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Blekinge Institute of Technology

Network relationship characteristics between companies operating in the Republic of South Sudan

By Price Conrad Enyai

Supervisors:

Ossi Pesämaa Shogo Mlozi

February 2013

This research project is submitted in partial fulfillment of the requirements for the award of Masters of Business Administration of Blekinge Institute of Technology

Master’s Thesis in Business Administration, MBA Programme

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Abstract This study focuses on issues in interorganizational cooperation to explain network relationships and their effect on company performance in South Sudan. According to the South Sudan National Bureau of Statistics, by June 2010, registered companies in the country were 7,333. Prior to this study, there appeared to be no study done concerning the interorganizational networks in South Sudan. The study builds on the recent studies of relations, selection and motives on organizational performance. The researcher adapted and modified the framework of previous researchers. This study excludes the mediating variable of interorganizational commitment to test directly the constructs of loose and soft, and hard explicit motives; trust and reciprocity, and expected goal congruence and network awareness. The sample consisted of randomly drawn 184 companies in South Sudan. The data was collected in December 2012 using questionnaires and analyzed using SPSS to distil descriptive data and conduct factor analysis. The research objectives are to test the effects on performance of: initial motives; criteria of selecting a partner; influence of trust, and the influence of reciprocity. The research question is: What effect does social capital capitalized from partner goals; selection, and motive have on organizational performance? To achieve the specific objectives of the research, six (6) hypotheses were developed. The study findings are that loose and soft-, and hard partner motives, partner selection and reciprocity had an effect on organizational performance while trust did not. The implications of this study are that companies that are involved in interorganizational networking and seeking to perform need to invest resources of time and money in clarifying their motives; learn from partners; select partners; match mutual goals; keep a database of potential partners; practice reciprocation, and build relationships that rely more on control and legally enforceable contracts. This study has contributed to the response to the main problem of lack of researched studies in interorganizational cooperation with in South Sudan. The study has blazed the trail for further study on the topic of interorganizational cooperation in the country. The specific contribution of the study is that it has confirmed that five of the conceptualized constructs affect organizational performance and trust does not affect performance in the Republic of South Sudan. The study has contributed to obtaining evidence of how these outcomes occur within this setting. Key words: loose and soft- and hard explicit motives, trust, reciprocity, network awareness, expected

goal congruence, organizational performance.

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Acknowledgements I express special thanks and appreciation to Ossi Pesämaa (PhD) of Blekinge Institute of Technology for his remarkable guidance and challenging ideas which have helped to shape the clarity of my conceptualization during the course of producing this work. I am exceedingly grateful to Shogo Mlozi (PhD) of Hanken School of Economics, Finland for guiding me through the methodological, theoretical and analytical issues during the course of this research. I acknowledge my brother and mentor Victor Avasi who has commented and helped me to proofread my writings and finally to my lovely wife Crystal Grace for the sacrifice and moral support extended during the period of study and during the production of this work.

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Table of Contents Abstract ......................................................................................................................................................... 2 Acknowledgements ....................................................................................................................................... 3 Table of Contents .......................................................................................................................................... 4 List of Tables ................................................................................................................................................ 5 List of Figures ............................................................................................................................................... 5 List of Abbreviations .................................................................................................................................... 6 Chapter 1: Introduction ................................................................................................................................. 7

1.1 Background and Context of the Study ................................................................................................ 7 1.2 Motivation and Rationale .................................................................................................................... 7 1.3 Overall Objective ................................................................................................................................ 8 1.4 Key Terminologies .............................................................................................................................. 8 1.5 Outline of the Study ............................................................................................................................ 9

Chapter 2: Theoretical Background and Hypotheses .................................................................................. 10 2.1 Literature Review .............................................................................................................................. 10 2.2 Understanding Companies and Networks ......................................................................................... 10 2.2.1 Organizational Performance .......................................................................................................... 11 2.3 Loose and Soft Motives .................................................................................................................... 12 2.3.1 Loose and Soft Motives and Organizational Performance ............................................................ 13 2.4 Hard Explicit Motives ....................................................................................................................... 13 2.4.1 Hard Explicit Motives and Organizational Performance ............................................................... 14 2.5 Expected Goal Congruence ............................................................................................................... 15 2.5.1 Expected Goal Congruence and Organizational Performance ....................................................... 15 2.6 Network Awareness .......................................................................................................................... 17 2.6.1 Network Awareness and Organizational Performance .................................................................. 18 2.7 Trust .................................................................................................................................................. 19 2.7.1 Trust and Organizational Performance .......................................................................................... 19 2.8 Reciprocity ........................................................................................................................................ 20 2.8.1 Reciprocity and Organizational Performance ................................................................................ 21 2.9 Conceptual Framework ..................................................................................................................... 22

Chapter 3: Research Design ........................................................................................................................ 23 3.1 Quantitative Study ............................................................................................................................ 23 3.2 Instrument ......................................................................................................................................... 23 3.3 Sampling and Data Collection Design .............................................................................................. 23 3.4 Design of Questionnaire ................................................................................................................... 24 3.5 Measurement of Variables ................................................................................................................ 25 3.5.1 Measurement of Loose and Soft Motives ...................................................................................... 25 3.5.2 Measurement of Hard Explicit Motives ......................................................................................... 25 3.5.3 Measurement for Expected Goal Congruence ............................................................................... 26 3.5.4 Measurement of Network Awareness ............................................................................................ 26 3.5.5 Measurement of Trust .................................................................................................................... 26 3.5.6 Measurement of Reciprocity .......................................................................................................... 26 3.5.7 Measurement of Performance ........................................................................................................ 27 3.6 Ethical Considerations ...................................................................................................................... 27

Chapter 4: Empirical Findings and Analysis .............................................................................................. 28 4.1 Descriptive Results ........................................................................................................................... 28 4.2 Results of the Model ......................................................................................................................... 28 4.2.1 Means, Standard Deviations and the Correlations ......................................................................... 29

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4.2.2 Exploratory Factor Analysis .......................................................................................................... 31 4.3 Test of Hypothesis ............................................................................................................................ 32 4.4 Validity and Reliability ..................................................................................................................... 33 5.1 Lessons .............................................................................................................................................. 35

Chapter 6: Conclusions and Recommendations .......................................................................................... 38 6.1 Contributions of the Study ................................................................................................................ 38 6.2 Implications....................................................................................................................................... 39 6.3 Limitations and Future Research ...................................................................................................... 39

References ................................................................................................................................................... 41 Appendix ..................................................................................................................................................... 52

List of Tables Table 1: Sample descriptive (N=184) ......................................................................................................... 28 Table 2: Spearman correlation, Means and Standard Deviation (N=184) .................................................. 30 Table 3: Exploratory Factor Analysis ......................................................................................................... 31 Table 4: Stepwise regression ...................................................................................................................... 33 Table 5: Internal reliability of the instrument ............................................................................................. 34

List of Figures Figure 1: A model showing hypothesized relationship of constructs ......................................................... 22

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List of Abbreviations A Acquaintances CEO Chief Executive Officer DRC Democratic Republic of Congo EFA Exploratory Factor Analysis EU European Union F Friends FDI Foreign Direct Investment H1 Hypothesis 1 H2 Hypothesis 2 H3 Hypothesis 3 H4 Hypothesis 4 H5 Hypothesis 5 H6 Hypothesis 6 IPO Initial Public Offering ISA International Strategic Alliance MBA Masters of Business Administration MNC Multinational Cooperation n Sample Size OP Organizational Performance Qn Question n (where n=1 to 20) R & D Research & Development RCP Reciprocity ROI Return on Investment S Strangers S.D Standard Deviation TRU Trust VC Venture Capital VO Virtual Organization

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Chapter 1: Introduction This study focuses on challenges of foreign companies related to cooperation and networking issues in the context of Africa. This chapter covers a synopsis of the study and acquainting readers with the context in which the study was undertaken. The structure of this thesis is given at the end of this section.

1.1 Background and Context of the Study In 2011 the economy of South Sudan opened up to investment having become the newest nation on earth. This followed the signing of the Comprehensive Peace Agreement in 2005, which brought an end to a decades-long conflict in South Sudan (World Bank, 2012). The country’s economy is attracting foreign investors. According to the South Sudan National Bureau of Statistics, by June 2010 registered companies in the Republic of South Sudan were estimated to be 7,333. They were reported to be in the industries of Agribusiness, Oil and Gas, Manufacturing and Services. International individuals and companies are investing in the South Sudan. No study hitherto has been done to analyze the loose and soft and hard explicit motives of these companies in South Sudan and whether the motives have an effect on organizational performance. It is not clear what role the application of preference transitivity plays in the selection of a local business partner to invest with in South Sudan and how it affects organizational performance. Furthermore it is not clear what opportunities companies in this country avail to interorganizational relations in terms of business prospects that are worth investing in and thus there is no clarity about how expected goal congruence of the companies involved impacts organizational performance.

1.2 Motivation and Rationale It is unclear whether companies in South Sudan coordinate resources and activities better than others and thus strengthen the participating companies and the industry structure (Gulati et al., 1999; Kogut, 1988). It is unclear whether cooperating companies outperform other companies (Ingram and Roberts, 2000). It is not clear yet to what extent interorganizational cooperation is successful in the country as a result of being well matched (Geringer, 1991; Dacin, Hit & Levitas 1997), or because of unclear motives regarding what companies can achieve in these networks. This issue is relevant in a number of ways. Entering into foreign environments means that the investing company’s existing knowledge and capabilities are often not applicable, and the company has to develop new knowledge and capabilities in order to succeed (Johanson & Vahlne, 1977, 1990; McDougall & Oviatt, 1996; Sapienza, Autio, George & Zahra, 2006). This implies that interorganizational trust is low or non-existent prior to two companies cooperating. While networking companies have been shown to perform better (Sampson, 2007; Shipilov, 2006), few studies moreover in other contexts only, examine theoretical models to obtain evidence of how these outcomes occur (Bolland and Wilson, 1994; Lee et al., 2004). While the growth in economic activity is impressive in South Sudan, there is a dearth of studies in the context to document how the emerging relationships develop to maturity and subsequently affect company performance in the market. No survey beyond the official records at the Bureau of Statistics (2010) of South Sudan has been conducted to show the growth in the number of formal businesses to date. In line with Pesämaa et al. (2010), there is no researched study available concerning the relationship between loose and soft motives and hard explicit motives; trust, reciprocity; partner’s selection represented by expected goal congruence and network awareness, and organizational performance within the context of interorganizational networks in the Republic of South Sudan. Hence companies in South Sudan continue to operate without definitive knowledge of how the constructs of loose and soft and hard partner motives; trust, reciprocity; partner’s selection represented by expected goal congruence and network awareness affect organizational performance in South Sudan. Entering new markets in foreign countries means a company is exposed to different uncertainties such as personal, financial, technical and institutional uncertainties. Many of these uncertainties are per se risks (Pesämaa et al., 2013).

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These constructs gave the researcher one point to entry an established paradigm of network relationships and its relationship towards performance. The constructs gave the researcher one point to entry an established paradigm of network relationships and its relationship towards performance. This practical quest led this thesis work towards works established in current research. The study is vital and supports knowledge to improve the human condition in the following categories:

i) Companies

The research will help company management to become more successful in managing risks having been made aware of the factors involved in partner selection and organizational direction.

ii) Study applicability in research area (knowledge) The research will add to the body of knowledge as it will reveal new insights into the way in which investors in the Republic of South Sudan relate and cooperate with their partners and other stakeholders. The study provides information which is currently not available. The findings will reveal insights into areas requiring further investigation, which will form a basis for future research.

iii) Immediate user The study will help members of the cooperating destination network to get revelation into the interconnectedness of loose and soft and hard partner motives; trust, reciprocity; partner’s selection represented by expected goal congruence and network awareness, and organizational performance in the Republic of South Sudan.

iv) Policy implication The study will provide a point reference for policy makers in the Republic of South Sudan to fine tune investor relationships and interorganizational companies’ performance through establishing or modifying investment regulations and guidelines.

Given, the input from earlier studies, risks entering foreign markets and the fact network relationship can support transformation of uncertainties to calculated risks this study propose following research question: What effect does social capital capitalized from partner goals, selection and motive have on organizational performance?

1.3 Overall Objective The study seeks to explain how risk management here defined as a network strategy influences organizational performance in South Sudan. The study empirically approaches challenges of foreign investors in relation to networking and partnership.

1.4 Key Terminologies Loose and soft motives are a company’s drive that guides organizational learning to become familiar with other companies and their business operations (Huggins, 2000; Pesämaa et al., 2010) hard explicit motives are a company’s drive representing concrete aspects of the types of exchanges that companies are seeking in networks and express an embedded ambition to gain control of input sources and what these companies want to know and specify in advance; control of costs, development, and obtaining financing. (Pesämaa et al., 2010).

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Trust is the reliance by one company on another entity based on the other entity’s honor. Trust is the expectation that an exchange partner will not engage in opportunistic behavior, even in the face of countervailing short-term incentives and uncertainty about long-term benefits. (Chiles & McMackin, 1996). Reciprocity is a mutual or cooperative interchange of favors or privileges; responding to a positive action with another positive action, rewarding kind actions. (Pesämaa et al., 2008). Network Awareness is the state of being knowledgeable of interorganizational states and processes: possessing information about the end-goal of the coordination process, what the starting point for coordination is and how to get to the end-goal from the starting point. (Vervest, van Heck, Preiss, & Pau (2004). Expected Goal Congruence refers to the degree to which companies believe that common goals can be achieved, after multiple interactions that help them understand each other’s constraints and opportunities. (Jap, 1999). Organizational Performance is the measure of success of a company in terms of financial health, business operations and organizational effectiveness. (Steer, 1975).

1.5 Outline of the Study The outline of this thesis is as follows: Chapter one introduces the study, its context, motivation and focus. Chapter two gives the theoretical background and hypotheses as captured in the literature review. Chapter three contains the methodology used in this study, detailing the design, measurement tools and data collection procedures. Chapter four contains the empirical findings of the study and analysis in connection to the conceptual framework in section 2.9. Chapter five hosts the discussion of the findings and their implications. Chapter six gives the main conclusions and recommendations of the study. Chapter 7 deals with the limitations of the study as well as the areas of further study.

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Chapter 2: Theoretical Background and Hypotheses 2.1 Literature Review Studies have been conducted in the field of interorganizational networking and its underlying factors to gain a better understanding of its strategic value. Early studies explored the reasons and evolution of the interfirm collaboration (Chandler: 1992; Wilson, 1994; Clarke & Hallsworth, 1994; Castells, 1996; Tidd, Bessant & Pavitt 1997; Kogut, 1988; Narula & Hagedoorn, 1999; Ingram & Roberts, 2000. Later studies examined interorganizational cooperation under globalization (Gulati et al., 1999; Tomkins, 2001; Sydow, 2003; Lee et al., 2004, Shipilov, 2006). The more recent studies have unpacked the role of relational, selection-based and motive-driven constructs on organizational health in the framework of interorganizational networking (Pesämaa, 2007; Lundin, 2007; Poria, 2007; Sampson, 2007; Pesämaa & Hair, 2008; Pesämaa et al., 2010; Moeller 2010; Wang, 2011; Kinduris et al., 2012). Building upon the recent studies the researcher sought to understand the relationship between loose and soft and hard partner motives; trust, reciprocity; partner’s selection represented by expected goal congruence and network awareness, and organizational performance in the setting of a third world country, South Sudan.

2.2 Understanding Companies and Networks A company is an organizational arrangement often involved in interorganizational networks (Pesämaa & Hair, 2008). It is a group of people, with production tools, located in given premises, which, employ people or and/or machinery to transform raw materials into goods and services, and sell them. According to Chandler (1992):

“A firm is a legal entity - one that signs contracts with its suppliers, distributors, employees and often customers. It is also an administrative entity, for if there is a division of labor within the firm, or it carries out more than a single activity, a team of managers is needed to coordinate and monitor these different activities. Once established, a firm becomes a pool of learned skills, physical facilities and liquid capital. Finally, ‘for profit’ companies have been and still are the instruments in capitalist economies for the production and distribution of current goods and services and for the planning and allocation for future production and distribution.” (p. 483)

The study assigns the meaning of the word ‘company’ to the terms such as enterprise, business, organization, business organization, business enterprise, and business companies. Pesämaa & Hair (2008) observed that companies do not exist and operate in isolation. Instead they work through during the course of conducting business. Cooperation has been established as one strategy that improves companies’ competitiveness (Pesämaa, 2007). Sydow (2003) cited in Moeller (2010) distinguishes between interorganizational networks and cooperation arguing that there are different definitions of networks. Business networks are differentiated as a special form of cooperation, whereas cooperation is a generic term for different forms of inter-organizational cooperation. Tomkins (2001) differentiated between collaboration: relationships, alliances and networks. A relationship is taken as the bedrock upon which an alliance is formed; a network is more complex and formed from configurations of alliances and relationships that range from intimate partnerships to simply buying and selling on a competitive basis or even just exchanging views and other information. Castells (1996) and Tomkins (2001) viewed large corporations as networks in themselves, where they have autonomous subunits, and different parts of a large organisation as having links into different external networks. Tidd et al. (1997) saw an organizational network as consisting of a number of positions or nodes, occupied by companies, business units, universities, governments, customers or other actors, and links or interactions between these nodes. In this study these distinctions were de-emphasized in the interest of pursuing an exploratory study of the subject within the context of South Sudan. Businesses and their autonomous subunits were regarded as the same entity to avoid duplication in the data of the study.

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In South Sudan a company is likely to face a number of challenges that constitute a risk to undertaking foreign investment. Thus interorganizational relationship offers a platform to manage and share risks, increase customer knowledge, gain access to international markets or search for another source of value/important resource enhancing company operations. According to Kinduris et al. (2012) companies form or join networks to reduce costs, increase flexibility, learn and share knowledge, access information and specialized work-force, develop innovations and/or obtain financing from governments or special funds. The study stresses that networking is especially important for small and medium size enterprises. This underscores the importance of interorganizational networking for the survival and viability of companies such as found in South Sudan. Thus the stakeholders in the collaborative networks include other local and international companies, customers, subcontractors, bankers, community contacts, family amongst others, each with its own interests and objectives. Clarke and Hallsworth (1994) suggested that interorganizational networking serves the purpose of establishing a quasi-oligopolistic market for the prevalence of cross-shareholdings among major companies, which makes this a highly networked environment. They state:

“The system seems to have developed into a highly controlled and mature market with little evidence of excessive, cut-throat competition between shopping centers, which has translated through to the location of developments (or rather the lack of them) on the ground. This might be viewed with some concern, as a possible affront to competition.” (p. 44).

This view is reinforced by Narula and Hagedoorn (1999) according to whom globalization has compelled firms to seek opportunities to cooperate, rather than seek to achieve majority control. They saw the increasing similarity of technologies across countries and cross-fertilization of technology between sectors, and the increasing costs and risks associated with innovation, as leading firms to utilize strategic technology partnership as a first-best option. Thus companies in South Sudan are likely to participate in interorganizational cooperation because of competition concerns, technological advantages and cost optimization, which are compelling motives. In this study, the researcher sought to understand whether organizational performance in the context of a third world country depended on partners’ motives; the fundamentals of social capital (Chung et al., 2000), and partner selection criteria. Specifically the researcher studied relationship between loose and soft partner motives and hard partner motives; trust, reciprocity; partner’s selection represented by expected goal congruence and network awareness, and organizational performance within the context of interorganizational networks.

2.2.1 Organizational Performance As good performance is most likely one of a company’s strategic priorities to pursue (Altinay & Okumus, 2010), it is important to first examine what other studies have to say about organizational performance. According to Gulati et al. (1999); Kogut (1988), Pesämaa et al. (2010) unless conflicts arise leading to collapse of the network, interorganizational networks coordinate resources and activities better than others and thus strengthen the participating companies and the industry structure. Approximately 70% of interorganizational cooperation effort ends in failure (Park & Russo, 1996; Pesämaa et al., 2010). Most failures are due to partners not being well matched (Geringer, 1991; Dacin et al., 1997), or unclear motives regarding what companies can achieve in these networks Pesämaa et al. (2010). Sampson (2007); Shipilov (2006) and Pesämaa et al. (2010) observe that while networking companies have been shown to perform better, few studies examine theoretical models to obtain evidence of how these outcomes occur (Bolland & Wilson, 1994; Lee et al., 2004). Delaney and Huselid (1996) suggest two ways to assess OP: financial and market performance. Mohr and Spekman (1994), Das and Teng (2003) Richard, Devinney Yip and Johnson (2009) view organizational performance as encompassing (a) financial performance such as: profits; return on assets, and return on investment (b) product market performance such as: sales, and market share, and (c) shareholder return such as: total shareholder return; economic value added. Dickson (1966) and

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Moeller (2010), give 23 commonly used financial and non-financial criteria that can be interpreted as the partners’ quantitative and qualitative performance measures that need to be evaluated. Ellram (1990, 1991) emphasizes the use of financial stability and economic performance; managerial, organizational, and cultural criteria. Vickery et al., 1999; Stock, Greis and Kasarda (2000) and Vivek and Ravindran (2009) view measurement of organizational performance in six aspects encompassing financial, and market based indicators. Thanassoulis (1993); Devinney, Yip and Johnson (2009), and Richard et al. (2009) advocate for use of nonparametric techniques as they represent the multidimensional nature of performance in a superior fashion to the traditional parametric alternatives. Tippins and Sohi (2003) proposed OP is measured on relative profitability, return on investment, customer retention, and total sales growth. What they appear to agree on is that organizational performance can be assessed by either financial- or nonfinancial- or both parameters depending on the motivation for measuring performance. An important aspect of interorganizational networking and organizational performance is linked to cooperation with supply companies. Supply though commonly associated with goods involves the outsourcing of goods, services and works as well. The understanding is that the good performance of suppliers supports organizational performance. Traditionally outsourcing has been associated with the pressure for cost reductions Kang, Wu, Hong and Park (2011). In the last twenty five years the objectives of outsourcing have grown to include the goal of seeking sustainable competitive advantage (Hätönen & Eriksson, 2009; ibid). Outsourcing performance includes both cost reduction measures and overall strategic value dimensions (Handley & Benton, 2009; Bengtsson, Haartman & Dabhilkar, 2009; Gilley & Rasheed, 2000; Varadarajan, 2009; Zhou & Li, 2010). According to Yamin, Gunasekruan and Mavondo (1999) and Vivek and Ravindran (2009), the presence of a company in the marketplace and its profit generation over time reflected in its performance. In the shorter time horizon, performance considers operational functions like productivity and efficiency. On the other hand according to Tan, Kannan and Handfield (1998) and Vivek and Ravindran (2009) performance in the long term means higher market share and greater profits for all the companies in the supply chain. The literature on interorganizational networks was silent on what actually goes on in terms of the production process in the local partner company as dictated by its strategic agenda in the post-formalization period of cooperation with a foreign investing partner company. It appears that researchers in the field of interorganizational cooperation take it for granted that whether a company is in a network or not it is not different from another company in its operations management to create value. In the light of this gap, this study assumes the generic economic definition of production as a process, the act of creating output, a good or service which has value and contributes to the utility of individuals (Kotler, Armstrong, Brown & Adam, 2006). It involves use of inputs; transforming them; generation of output goods and services and feedback for improvement of the production process. This study explored dimension to tease out the relationship with interorganizational networking and the conceptualized study constructs.

2.3 Loose and Soft Motives Pesämaa et al. (2007, 2010) were of the opinion that partner selection is based on appraisal of the loose and soft cooperative motives. They are necessary for forming networks and influencing how partners are selected (Parkhe, 1993; Volery, 1995; Rosenfeld, 1996; Huggins, 2000; Gounaris, 2005). Learning a local partner’s know-how, knowledge and technology development listed by Glaister and Buckley (1996) and Dong and Glaister (2006), are examples of early reference to loose and soft motives. Huggins (2000) and Pesämaa et al. (2010) regard loose and soft cooperative motives as involving becoming familiar with other companies; representing issues related to business operations. Thus, companies display specific motives and assumptions about partners’ trustworthiness when entering networks. Firms search for partners whom they can trust based on their own hard and loose and soft cooperative motives. According to Elko, Jeffrey, Peter and Keith (2010) there are motives that are natural candidates for partners to couple together. They view knowledge/technology development and market power as motives that are often coupled together and that despite having multiple motives, partners in joint ventures often have similar motives hence, even though partners have multiple motives there might be an incentive for alignment in these cases. In situations where firms have three

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or more motives it can become difficult to align the wishes of partners and find a joint venture deal structure that satisfies the cooperating partners. Businesses in developing economies exhibit self-interest too. Peng (2003) and Zhao et al. (2009), while studying interorganizational networking in the Chinese context, observed that firms were faced with two strategic choices to obtain resources namely to develop competitive resources and capabilities in-house and to utilize external sources, such as interorganizational relationships, to obtain needed assets. They argued that managers may rely on external sources of knowledge in the early phase of transitions when they lack managerial expertise to manage uncertainties, and in the face of other institutional constraints. Thus entering into foreign environments means that the investing company’s existing knowledge and capabilities are often not applicable, and the company has to develop new knowledge and capabilities in order to succeed (Johanson & Vahlne, 1977; McDougall & Oviatt, 1996; Sapienza et al., 2006; White, 2005). Mowery, Oxley & Silverman (1996); Grant and Baden-Fuller (2004) and Lui (2009) agreed that an organization acquires and accesses knowledge from a partner to extend its own knowledge base. Szulanski (1996), Szulanski et al. (2004), Lui (2009) acknowledged that learning is often difficult to undertake, as knowledge is sticky to move between partners. There is always the threat that an opportunistic partner may become a competitor through knowledge spillover. (Khanna et al., 1998; Becerra et al., 2008).

Loose and soft motives are evident in supplier/company relations too. According to Lui (2009), a supplier possesses specialized knowledge in production which is beyond the buyer’s knowledge domain. A buyer needs to access this knowledge for an efficient production of goods. In addition a supplier possesses knowledge of the market based on its business relationships with other buyers. A buyer can benefit from this knowledge if this is acquired from the supplier and integrated into the buyer’s own knowledge domain. Thus, a buyer needs to access and acquire the knowledge of a supplier. The interest of the buyer is to take the two learning objectives into consideration when designing the governance mechanisms with its supplier. (ibid.). The motives of international stakeholders in seeking business partners in South Sudan are not articulated in literature.

2.3.1 Loose and Soft Motives and Organizational Performance The research of Pesämaa et al. (2010) proposes that stronger awareness of motives and balanced preferences among partners reduces uncertainty. This is due to a partner knowing what to expect and how other partners are likely to perform when the relationship progresses from no interaction to full interaction and is then further locked into a series of commitments. Literature on the formation of interfirm collaborations typically assumes that uncertainty leads to the formation of embedded transactions (Chung et al., 2000; Gulati & Gargiulo, 1999; Meuleman et al., 2010). Baum, Rowley and Shipilov (2005) found that organizations’ performance relative to their aspiration levels, determines willingness to bear the risk of collaborating with unfamiliar partners. According to Moeller (2010), there are different performance measures and criteria in cooperation research: one approach to measure cooperation performance is to use intangible, rather than subjective measurement dimensions such as the business partners’ “perceived satisfaction” or “achievement of objectives.” This approach facilitates measurement of loose and soft motives. Pesämaa et al. (2010) found that loose and soft motives had an effect on organizational performance on companies in the US. This is yet to be studied in the case with South Sudan. Accordingly, the researcher proposes: Hypothesis H1: Loose and soft motives has an effect on performance

2.4 Hard Explicit Motives According to Edquist (1997) and Pesämaa et al. (2010), motives reflect the basic need for cooperation to evolve in the first place. Successful companies pursue explicit and conscious motives in their actions and strategies. Pesämaa et al. (2006, 2007b) found that hard cooperation motives (share costs,

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development and financing) significantly guide partner selection in the network. According to Baum and Ingram (2002), the existence of interfirms is a response to dependence. They explain that organizations prefer to transact with others of known reputation, and tend to mimic one another, particularly when environmental uncertainty is high. Osborn and Hagedoorn (1997) are of the view that each participant in an interorganizational network may have a clear-cut mission for an alliance or a network, but the intentions of the participants in a given alliance or network may differ widely. Alliances and networks are strategically determined, and they emerge as natural by-products of corporate activity. They show the reach of a firm and the grasp of its limitations. Thus companies acknowledge their limitations by entering relations with complimentary partner companies. In Pesämaa et al. (2010) hard cooperative motives include co-production, co-development and co-financing representing concrete aspects of the types of exchanges that companies are seeking in networks and express an embedded ambition to gain control of input sources; what these companies want to know and specify in advance; control of costs, development, and obtaining financing. Kinduris et al. (2012) shares a similar view. Glaister and Buckley (1996) and Dong and Glaister (2006) discussed motives which later studies built on for entering a partnership. Such motives include risk reduction; economies of scale and/or rationalization; complementary technologies and patents; co-opting or blocking competition; overcoming government-mandated investment or trade barrier; initial international expansion; vertical quasi integration, and drawing on existing fixed marketing establishment. These span the spectrum of hard explicit motives. Organizations that are not profit oriented exhibit hard explicit motives too. According to Ngamassi, Zhao, Maldonado, Maitland and Tapia (2010), two reasons characterize collaboration relationships among members of the Global Symposium community namely, location of operation, and resources. They add that every interorganizational network is clustered into groups of agencies centered on specific needs. Thus in selecting partners, companies search for specific types of companies. According to Berg (2012), companies tend to network with other companies where the interactions are deemed to be beneficial in terms of the loose and soft and hard cooperation motives described in Pesämaa et al. (2010).

2.4.1 Hard Explicit Motives and Organizational Performance Pesämaa et al. (2010) found that loose and soft cooperative motive was directly related to interorganizational commitment which itself is based on promises to exchange as well as the intention to allocate more resources and share more operations with other companies in the network. Thus success is based on a long-term shared future of organizational performance for the networked companies. Again Pesämaa et al. (2010) found that third cooperative motive, directly affects reasons to share costs, product development and financing, which indicates that, in this situation, the company is expecting something in return for it cooperative efforts. Thus, success likely is related to motives involving wanting to get something back. In this study, the realization of partner motives is the goal of interorganizational cooperation and effort. Understanding how such discipline-specific measures load onto the dimensions of organizational performance and the interrelationships between specialist measures is essential to understanding the relationships between multiple organizational actions (Richard et al., 2009). It is a costly and time-consuming process to establish a successful partnership. Both partners need to make more commitment, mutual adaptation, and contribute learning and resources (Wang & Kess, 2006). Extending the definition of Mael and Ashforth (1992), supplier-buyer identification is the perceived oneness of one partner with an organization and the experience of the organization’s successes and failures as one’s own. Corsten, Gruen & Peyinghaus et al. (2011) agreed that supplier-to-buyer identification fosters superior operational performance. It does so by enhancing trust, supplier relation-specific investments, and information exchange. Supplier relation-specific investments and information exchange play different but complementary roles in influencing operational performance. (ibid.). Corsten et al. (2011) found that the perceived oneness of a supplier with a buyer stimulates mutual trust, supplier relation-specific investments and information exchange, which lead to higher operational performance and relational competitive advantage. Pesämaa et al. (2010) found that hard

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explicit motives had an effect on organizational performance on companies in the US. It is not obvious that this is the case with South Sudan. Accordingly, the researcher proposes: Hypothesis H2: hard explicit motives has an effect on performance

2.5 Expected Goal Congruence According to Levine and White (1961) and Lundin (2007) goals are an important aspect of interorganizational relationships. Sammadar et al (2006) refers to goal congruence as the degree to which the partner companies are jointly involved in the achievement of a goal. Schmidt and Kochan (1977), while studying community organizations and local offices of the US Training and Employment Service Compatibility, found that goals are found to be positively associated with cooperation. In Anumba, Siemieniuch and Sinclair (2000), companies in a network have various goals, but there should be commonality on the goals that are important to the efficient functioning of the relationship. O’Toole (1983), in a study of interorganizational implementation of labor market policies in Sweden and the Federal Republic of Germany, indicated that perceived common interest increases cooperation among local actors. Easton (1997), Galbraith (1998) and Moeller (2010) view partner selection as aimed at identifying network partners’ potential for creating a joint value. Hence partner selection is linked to business network formation and refers to strategy, structure, and partner decisions. The formation of business networks depends on identification of value-adding strategies to get benefits in the process of providing goods and services (Moeller, 2010). Ellram (1990, 1991) observed that selecting potential network partners should be based on an analysis and evaluation of such criteria, as well as the overall fit. In respect of the latter, partner compatibility is a pivotal factor determining the behavior, strategy, and structure in business networks (Child and Faulkner, 1998; Dekker, 2008; Moeller, 2010). In studying franchise selection decision making, Altinay (2006), Altinay and Wang (2006), Altinay and Okumus (2010) hold that interrelated antecedents such as a company’s strategy, leadership, cross-functional interface, organizational structure, and communication play an important role in the franchise partner selection. Different organizational parameters interact and exert influence upon each other while a franchise organization decides to choose the most appropriate franchise partner. According to Shrivastava (2005) there opportunities exist for combining the Internet's services and resources into interorganizational services. Collaborative ventures, or virtual organizations, continue to encourage strategic alliances among groups of organizations that share services electronically to satisfy mutual business goals. As such each organization can maintain its autonomy except for the mutually agreed commitments of alliances.

2.5.1 Expected Goal Congruence and Organizational Performance Pesämaa et al. (2010) posit that interorganizational networks are the outcome of individuals in firms working together in cooperative groups involving both formal and social relationships. The individuals develop lasting relationships because they share time, interests, goals, and industrial, geographical or other type of relationships. Shared goals and interests become an observable characteristic built upon constructs of the relationship. Cooperative efforts have strategic implications (Poria, 2007; Pesämaa et al., 2010). Lundin (2007) in a study of Swedish Public Employment Service offices and municipalities found that trust is not required for resource interdependence to affect cooperation, and the effect of trust is not dependent on the organizations’ mutual dependence. The results of the study show that trust and goal congruence must exist concurrently if joint actions are to take place. Consequently if a management only focuses its strategy on increasing cooperation on the organizations’ objectives or the level of trust between them, it will fail. (ibid.) According to Moeller (2010) strategic fit can be used to reduce the risk of potential conflicts. This is achieved by matching institutional partners to be of the same size and/or have equal power. In this way partners have an equal need for resources and capabilities and their goals are complementary or not in

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conflict, which can generate cooperative competitive advantages. Such configurations are driven by people with in the organizations. Networks of cooperating firms outperform other firms in the context of the tourism industry (Ingram & Roberts, 2000; Pesämaa et al., 2010). According to Venkatraman and Ramanujam (1986); Hamon (2003), Ho (2008), organizational performance (OP) is an indicator which measures how well an enterprise achieves their objectives. Such performance can be assessed by an organization’s efficiency and effectiveness of goal achievement (Robbins & Coulter, 2002; Ho, 2008) Pesämaa et al. (2010) asserts that expansion in relationships starts when relationships begin and continues until they are locked into definite positions. Baum and Ingram, 2002 viewed the development of an organizational network as a staged process that grows into distinct network organizations that vary in their degree of functional integration. Stable interfirm relationships cause rivalry to shift from company to the network organization level. Thus, in a network organization, the outcomes for companies may be fundamentally intertwined with other companies that belong to the same network organization. The success of cooperative relationships is influenced by interorganizational commitment, which is a long run goal of networks (Pesämaa & Hair, 2008). Furthermore, evaluation provides the adaptability and responsiveness that are important preconditions for successful business networks. According to Stuart, Hoang and Hybels (1999) the rate of initial public offering (IPO) and the market capitalization at initial public offering (IPO) of venture-capital-backed biotechnology companies showed that privately held biotech companies with prominent strategic alliance partners and organizational equity investors go to IPO faster and earn greater valuations at IPO than companies that lack such connections. Lundin (2007) found that expected goal congruence had an effect on organizational performance on companies in the Sweden. This is yet to be studied in the case with South Sudan. Accordingly, the researcher proposes: Hypothesis H3: Goal congruence has an effect on performance

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2.6 Network Awareness Moeller (2010) is of the view that partner selection is associated with engaging negotiation and considering decision parameters concerning finance, contracts, information exchange, and organizational structures. Based on the evaluation of the findings, a business investments decision is taken. The model in Pesämaa et al. (2010) takes into account that motives and partner selection lead to uncertainty, which affects the way partners are selected. If firms could identify partners with specific knowledge and/or skills in advance, there would be less risk in partner selection. But establishing relationships requires time and effort, has a high likelihood of failure, and is therefore risky (Park & Russo, 1996, ibid.). Thus companies endeavor to learn about risks and attempt to establish safeguards against them as they enter and operate in interorganizational networks. According to Li et al. (2008), when examining how to control the threat of knowledge leakage and retain their core proprietary assets in an R&D alliance, companies employ three strategies: creating a secure governance structure; narrowing the scope of alliance activity, and partner selection. The latter construct involves companies evaluating three important preference transitivity strata implying that friends (F) are preferable to acquaintances (A), who are preferred to strangers (S). Wang (2011) held that in the foreign direct investment (FDI) network, transitivity represents that if firms in country i invest in country j, and firms in country j invest in country z, then firms in country i will invest in country z. The study found that transitivity plays a role on formation of FDI linkages, which implies that previous direct and indirect FDI experience does matter in FDI linkage formation. Because investors have understood and trusted their FDI target from their previous FDI collaboration, when they plan to make new investment abroad, they prefer to choose firms in the locations that they understand and trust. (ibid.). According to Gulati (1999) organizations enter alliances with each other to access critical resources, but they rely on information from the network of prior alliances to determine with whom to cooperate. The probability of a new alliance between specific organizations increases with their interdependence, and with their prior mutual alliances, common third parties, and joint centrality in the alliance network. Moeller (2010) sees partner selection as continuous positive and negative partner evaluation leading to preserving or terminating the cooperation between them, thereby permanently protecting the network from opportunistic behavior by the partners. Pesämaa (2007) found that both task and partner related criteria are important and positively associated with trust between tourism companies. Granovetter (1985), Gulati and Gargiulo (1999), Chung et al. (2000), Podolny (2001) and Meuleman et al. (2010) agree that relational network theory highlights how firms prefer to work with partners with whom they have an embedded relationship so as to reduce risk and uncertainty associated with interorganizational exchange. Embeddedness can lead to the creation of trust, information sharing routines, and joint problem solving between parties (Gulati, 1995b; Uzzi, 1997). Dekker (2008) found that partner experience from prior ties moderates the e ects control problems. In addition, partner selection and formal governance are found to be used as complements instead of substitutes in coping with interfirm control problems. The study confirmed findings that prior ties between exchange partners enable the use of governance arrangements to be reduced. This shows that network awareness strengthens trust-driven cooperation. Podolny (1994) and Meuleman et al. (2010), posit that market uncertainty induces investment banks to engage in repeat transactions with past partners, and to favor those with a similar status. Meuleman et al. (2010) sees partner selection as an important governance mechanism in interfirm alliances and recommend that future research needs to undertake a systematic analysis of partner selection in the heterogeneous contexts of alliance relationships. Osland, Taylor & Zou (2001) found that international joint ventures may be more appropriate for internationally-experienced US companies than for novice companies. New companies ought to be careful about selecting joint ventures as a mode of entry. This is because of the difficulty new companies face in selecting appropriate partners and managing complex joint venture relationships, firms that are familiar with the local situation, and that have experience in managing joint ventures, may be best suited to use cooperative arrangements. According to Li and Ferreira (2008), there are high risks characterizing international strategic alliances (ISAs). Engaging repeatedly with the same

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partner reduces transactional hazards. They found that US multinational corporations (MNCs) forming ISAs requiring higher extent of technological commitments are more likely to select their prior partners. The companies are more likely to select prior partners for ISAs when there is a larger institutional distance between the partners’ countries of origin. (ibid.). In addition Tesdahl (2010) on interorganizational cooperation between faith-based organizations confirmed the negative influence of physical distance on forming collaborative ties. They found that distance strongly shapes who will tend to collaborate even after controlling for race, denomination, contact with organizers, and activity level within each organization. Sorenson and Stuart (2008) and Meuleman et al. (2010) view the underlying characteristics of the transaction in which firms participate as one of the drivers of partner selection decisions. According to Dekker (2008), in the study on partner selection and governance design in interfirm relationships, the time spent by buyers on searching for and selecting an adequate supplier is explained by transaction size and asset specificity, while prior ties enable firms to reduce search time. The study suggested that buyers with prior ties with their supplier used the partner selection phase to mitigate concerns associated with larger and more uncertain transactions, while the main purpose of governance design was to coordinate larger transactions with more interdependent tasks. In contrast, firms without prior joint experience designed governance structures more in response to concerns originating from asset specificity and dependence, while in their supplier selection e orts they were only responsive to transaction size. Van de Bunt and Groenewegen (2007) found that companies have a preference for high status partners and they do not rely on transitivity. Furthermore, companies have a preference for partners that belong to the same groups of organizations they belong to in terms of partnerships, but with whom they do not collaborate yet. Moreover Elko et al. (2009) found that prior alliance experience does not play a role in the reason why firms enact joint ventures. This seeming contradiction has not been resolved in the literature.

2.6.1 Network Awareness and Organizational Performance Ritter, Wilkinson, and Johnston (2002) argued that a company’s ability to develop and manage relations with suppliers, customers and other organizations and to deal effectively with the interactions among these relations is a core competence of a company - one that affects a company's competitive strength and performance. Moeller (2010) found that partner selection has effects on trust, opportunism, and commitment. The study shows that selection of a partner is a critical managerial control task within business networks, as appropriate selection is a threshold condition for a successful business network. Dickson (1966) views mismatches in strategy, structure, and culture as potential conflict areas that represent a permanent risk of opportunistic behavior. The study recommends continuous evaluation of potential and existing partners by means of a partner fit analysis as a necessary precondition for successful business networks. According to Madhok and Tallman (1998); Todeva and Knoke (2005), Altinay and Okumus (2010), highlight the importance of partner selection since failing to select the right partner is a major cause of failure of collaborative relationships leading to adverse monetary and strategic effects. For example franchisors have to select franchisees that will adopt a system-wide standard outlook for their individual activities to contribute to the attainment of franchise system goals (Taylor, 2000, ibid.). This is vital to the success of the franchise system which involves the transfer of a business template from the franchisor to franchisees (Grant, 1985, ibid). Poor franchise recruitment can lead to de-motivation and lack of commitment on the part of the franchisee and refusal to follow the franchise system (Dewhurst & Burns, 1993; ibid.). While the literature indicates that deliberateness is selecting an interfirm partner is indispensible to assure successful business performance, it is still not clear how applicable this finding is to South Sudan. Ritter et al. (2002) found that network awareness had an effect on organizational performance in terms of network centrality of companies in Germany. This is yet to be studied in the case with South Sudan. Accordingly, the researcher proposes:

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Hypothesis H4: Network awareness has an effect on performance

2.7 Trust According to Zand (1972), Chiles and McMackin (1996), trust is the of increasing one party’s vulnerability to the risk of opportunistic behavior by an uncontrolled transaction partner, a situation in which the cost of violating trust exceeds the benefits of upholding trust. Sako (1992) defines trust as a mechanism to achieve predictability in co-operation. The study views trust in three ways namely; contractual, knowledge and goodwill trust, each of these indicating the increase in depth of trust between organizations. Pesämaa et al. (2008) found that, interpersonal commitment (IPC) fully mediates the relationship between trust and interorganizational commitment. Thus trust is held in individuals who are part of organizations. It follows that if people do not trust each other, interorganizational trust is affected. Hallikas and Ojala (2011) view trust as a basic element in networks and partnerships that varies in different kinds of relationships. Chiles and McMackin (1996) identified trust as having an effect on minimizing transaction costs. Dasgupta (1988) posits that some degree of risk must be present so that there is a test of trust. Hallikas and Ojala (2011) note that without vulnerability there is no need to trust. One partner cannot tell whether or not another partner will act opportunistically. This makes transaction costs to increase as the partners invest in safeguards against potential opportunistic behavior. Van der Meer-Kooistra and Vosselman (2000) assert that the presence of trust between co-operating parties is important in situations characterized by uncertainty and strong dependencies between the parties owing to specific investments. Chiles and McMackin (1996) recognize that the subjective risk of any transaction is influenced by the risk appetite of the firm's managers and the degree of trust between partners. The perceived risk of opportunistic behavior by another partner to a transaction involving asset-specific investments will be influenced by the risk preferences of a firm's managers and the level of trust in the relationship. Risk management is a set of actions taken by corporations in order to alter the risk arising from their primary line(s) of business (Cummins, Phillips & Smith, 1998). As such risk management is an expression of tentative trust which should improve as the interorganizational relationship grows. Rolof (2007) posits that stakeholder management is vital in order to foresee changing expectations and to detect conflicts before they threaten the corporation. Meuleman et al. (2010) found that relational embeddedness is less important for selecting partner firms when potential partner firms have established a reputation in the organizational community. Presumably reputation is linked to trust arising from the past track record. The entry into the South Sudan markets comes with numerous risks such as loss of financial resources or leakage of trade secrets but the contextual risks are yet to be fully unpacked and understood.

2.7.1 Trust and Organizational Performance O’Toole (2003) and Lundin (2007) agreed that trust and goal congruence must exist simultaneously in order to promote joint actions and that if organizations do not trust each other, similar priorities do not matter. A shared interest can be a powerful facilitator of cooperation, whereas diverging objectives may decrease cooperation (ibid.). Miller (1992) viewed risk as the threat of variance in corporate performance that cannot be forecast before commitment. When trust is partial, control mechanisms are activated. DiRomualdo and Gurbaxani (1998) were of the view that appropriate control mechanisms are necessary for the effective implementation of specific outsourcing strategies. In discussing outsourcing alliances in China, Li et al. (2008) found that the acquisition of tacit knowledge through inter-firm cooperation impacts on the use of control mechanisms. According to Shrivastava (2005), Virtual Organization (VO) operations management requires regulated access to service resources. This ensures that participating organizations policies on resource-sharing occur securely and with integrity. This is difficult to achieve as each potentially accessible organization might not unconditionally trust the others. Accordingly, all organizations in a VO require strictly controlled and policed interactions. Business process relationships require protected trust management procedures for terms and conditions, rules that typically govern a conventional business partnership laid down in a paper-based contract and quality of service.

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According to Russo and Vurro (2010), companies that engage in internal exploitation tend to balance such learning orientation with explorative interorganizational agreements. Consistently, those companies engaged in external exploitation tend to balance it with an internal focus on exploration, at least in the case of exploitative alliances involving familiar partners. This appears to confirm that trust and reciprocity are essential for renewing of cooperation agreements. Moreover, results confirm that such complementary cross-boundary strategies improve a company's innovative performance. According to Li, Eden, Hitt and Ireland (2008), when examining how to control the threat of knowledge leakage and retain their core proprietary assets in an R&D alliance, companies employ three strategies: creating a secure governance structure; narrowing the scope of alliance activity, and partner selection. Chen, Park and Newburry (2009) and Kang et al. (2011) are of the view that organizational control plays a key role in strategy implementation. Hartmann, Trautmann, and Jahns (2008), Narasimhan, Narayanan, and Srinivasan (2010) indicated that outsourcing strategies and organizational practices, such as failure-prevention practices and performance-enhancing practices are linked. According to Altinay and Okumus (2010), an expanding franchise organization is committed to empower its entrepreneurial organizational members. At the same time it has to control the overall integrity of the franchise system and preserve the brand reputation. This explains the control-oriented centralized mode of franchises. However, such a structure creates tension and frustration among potential franchise partners and key organizational members who work with different cultural mindsets. Feelings of mistrust can arise in such situations. To facilitate decision making, an international franchise organization needs to be tolerant to the differences of the mindsets of parties involved and establish clear linkages between these diverse views and the organization’s strategic priorities. (ibid.). Pesämaa et al. (2010) found that trust had an effect on organizational performance on companies in the US. However in the case with South Sudan this is yet to be confirmed. Accordingly, the researcher proposes: Hypothesis H5: Trust has an effect on performance

2.8 Reciprocity A study by Fassin (2012) shows that in the short term, a company should take account of the deserved rights and expectations of its various constituencies in order to balance their own and their stakeholders’ divergent interests. Pesämaa et al. (2008) found that unlike trust, reciprocity is directly related to interorganizational commitment and is not mediated by interpersonal commitment. The study by Pesämaa et al. (2010) found that sustained interorganizational commitment did not depend significantly on trust. According to the study, after selecting partners, companies experience two types of relational consequences, trust and reciprocity that represent an expanded state that occurs under full interaction. Cooperating companies use contracts to initially enforce commitment to reciprocate in the networking relationship. Dwyer et al. (1987) Jap and Ganesan (2000) and Moeller (2008) view partner selection as a pre-contractual mechanism that is triggered by signing a contract leading to a post-contractual mechanism. According to Lui (2009) the governance mechanisms of competence trust and formal contract facilitates interorganizational learning. Inkpen (2000), Dyer and Chu (2003), Muthusamy and White (2005) and Lui (2009) concur that trust in a partner’s competence creates a collaborative social context conducive to information sharing and learning. Makhija and Ganesh (1997), Srinivasan and Brush (2006) and Lui (2009) are of the view that formal contracts aid learning objectives by specifying the commitments and expectations of partners. Vlaar, Van and Volberda (2006, 2007) suggest that formal contracting clarifies terms, roles and responsibilities and so serves as a means to make better sense of an interorganizational relationship. It is the work of the relating parties to manage both the functions and dysfunctions of formalized controls. Inkpen (2000) was of the view that improved understanding between parties enhances knowledge assimilation, a loose and soft motive. Thus formal contract is likely to plays a stronger role than competence trust for knowledge acquisition. (Vlaar, Van & Volberda, 2007).

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Beckman, Haunschild, Philips (2004) found that companies form new relationships with new partners as a form of exploration, and form additional relationships with existing partners as a form of exploitation. Partner selection is a process and part of it commences before interaction and is initiated to decrease risk (Pesämaa et al., 2010). This is similarly evident in studies involving venture capital (Sorenson and Stuart, 2008). The entry of a company into the South Sudan comes with numerous risks such as loss of financial resources or leakage of trade secrets and so is likely to start at the level of mistrust. Besides, the future host partner will not yet have had a chance to return the favors to be extended by the yet-to-cooperate partner. Reciprocity at that stage is not possible.

2.8.1 Reciprocity and Organizational Performance Burt (1992), Mohr and Spekman (1994), Chung, Singh and Lee (2000), building on the work of Kandel and Lazear (1992), agree that trust-based relationship with repetitive exchanges is beneficial for long-term partners because of the sharing of opportunities and valuable information. According to Meuleman et al. (2010), mutual monitoring is necessary when agents pursue self-interest in the accomplishment of joint tasks; when the contributions of each partner affect the welfare of the rest of the team, and where partners are able to make performance-related choices that affect the group rewards received. Thus monitoring and control by the investing partners is a key success factor in optimizing the performance of companies. Wang and Kess (2006) found that in partner selection of international joint ventures task-related and partner-related dimensions apply to distributor relationship. The study holds that a distributor relationship is a product-tied relationship, and product innovation can be used as an approach for performance improvement in distributor relationship. Vivek and Ravindran (2009) found that supplier performance was modeled well by timely deliveries; dependable delivery, and supply of high quality materials goods. They found that the suppliers' performance influences organizational performance significantly. The study explained that this could be due to the fact that other variables like customer satisfaction, lean practices and information flows influence the organizational performance, a topic for further research. Pesämaa et al. (2010) found reciprocity had an effect on organizational performance on companies in the US. This is yet to be studied in the case with South Sudan. Accordingly, the researcher proposes: Hypothesis H6: Reciprocity has an effect on performance.

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2.9 Conceptual Framework

EXPECTED GOALCONGRUENCE

LOOSE AND SOFTMOTIVES

HARD EXPLICITMOTIVES

NETWORKAWARENESS

PERFORMANCE

TRUST

RECIPROCITY

H1

H2

H3

H4

H5

H6

Figure 1: A model showing hypothesized relationship of constructs

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Chapter 3: Research Design This section is about the approach to the study. The aim of this chapter is to describe the research methodology used to investigate how social capital capitalized from partner goals, selection and motive affects organizational performance. This chapter discusses the research design, development of the instrument, sampling, data collection, and ethical considerations. Research methods, otherwise known as research designs are of different types. Some studies combine the elements of different research designs such as experiment, quasi-experiment, correlational study, longitudinal study, cross-sectional study, survey, interview, case study, naturalistic observation, and/or demonstration. (Johansson, 2002). The main difference between the experimental and other designs is that the former employs random sampling while latter employs non-random sampling to assign members to study groups. A quantitative study design was adopted and a single survey conducted by self-administered questionnaire to measure the constructs described in the conceptual framework.

3.1 Quantitative Study According to (Trochim, 2005; Hair et al., 2010), research design provides the glue that holds the research project together. A design is used to structure the research, to show how the major parts of the research project -- the samples or groups, measures, treatments or programs, and methods of assignment -- work together to try to address the central research questions. According to Bryman (2004), choices of research strategy, design, or method have to be dovetailed with specific research question(s) being investigated. The study employs a quantitative design to; investigate the relationship between loose and soft and hard partner motives; trust, reciprocity; partner’s selection represented by expected goal congruence and network awareness, and organizational performance. The study measured the level of contribution. According to Trochim (2005) and Hair et al. (2010), the survey design is one of the most common forms of research. The survey approach was selected because the researchers did not intend to administer a program or intervention. The study would therefore benefit from self-reports by key informants in the selected organizations that capitalized on their perceptions and experience captured during the survey.

3.2 Instrument A survey is a structured list of questions presented to people whose responses are analyzed using qualitative and/or quantitative techniques. Surveys may be written or oral, face to face, over the communications or internet. It is possible to survey large numbers of people at a low financial and time cost. However the data quality may be lower than that obtained from other methods because people do not always answer questions accurately or fully. This study was based on the survey design with its advantage of relatively low financial and time costs. Given the geographical diversity of South Sudan, the cost of face to face interviews would have been prohibitive. Setting up an experiment would not be possible as it would involve developing and intervention. The intervention would then have to be tested on investors. All other designs would be time consuming to apply therefore the survey design was upheld despite the potential challenges pointed out above.

3.3 Sampling and Data Collection Design Sampling is the process of selecting units such as people or organizations from a focal population so as to studying the sample and fairly generalize the results back to the population from which they were chosen. (Trochim, 2005; Hair et al., 2010). The researcher used an empirical approach in studying a randomly selected sample of companies in South Sudan to determine the interaction of the focal constructs (i.e. motives, and partner selection) and relationships in interaction (i.e., trust and reciprocity) that the researcher suspected had an effect on company performance in the context of the study.

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The units of analysis of the study were organizational relationships. In the measurement of organizational performance, realization of partner motives and risk management, an organization was the sampling unit. This study was conducted in an open environment with no need to blind the respondents from influencing each other’s responses. Questionnaire response time was minimized to mitigate challenges that could arise due to interfirm consultations on responses. The questionnaire (see appendix) is designed from an established instrument in Pesämaa et al. (2010).

Given the one-shot measurement used in the study, the researcher resorted to random sampling to minimize effects of bias in the study and strengthen its external validity further. In Hair et al. (2010) external validity refers to the approximate truth of conclusions that involve generalizations. It is the degree to which the conclusions in a study would hold for other companies in other places and at other times. Drawing a sample using random selection, from a population can help to improve external validity. The other way is to make sure that the dropout rates of respondents are low. (ibid.).

Trochim (2005) gives five methods of random sampling namely simple, stratified, systematic, cluster and multistage sampling. It is possible to combine the first four methods in a variety of useful ways that help to address the sampling needs of a given study in the most efficient and effective manner possible leading to multi-stage sampling. Multi-stage random sampling was used to determine the coverage of the study. The choice of sampling strategy was on account of the large geographical size of South Sudan that would render the study too expensive to carry out. According to the National Bureau of Statistics in the official South Sudan Statistical Yearbook (2011), South Sudan is divided into ten states, namely Northern Bahr el Ghazal; Western Bahr el Ghazal; Lakes; Warrap; Western Equatoria; Central Equatoria; Eastern Equatoria; Greater Upper Nile: Jonglei; Unity, and Upper Nile.

Out of 10 states in South Sudan, three were chosen by blind selection of slips of rolled-up paper on which the name of a given province was written. The states selected were Central Equatoria State; Unity State; and Upper Nile State. The names of the companies within the selected list were pooled together for a further stage of random picking using systematic sampling.

The sample size, n selected by systematic random sampling consisted of 184 companies engaged in interorganizational networks with international partners involved. This sample is 21 companies more than the 163 companies that would be required at a confidence interval of 10 and 99% level of confidence, given a population size of 7,333 companies, the sampling frame consisting of the list of companies on the roll at the Sudan Bureau of statistics in South Sudan (ibid.). According to Hair et al. (2010) the larger the sample size, the more the answers truly reflect the population.

Consequently, data was collected from the three randomly selected states. The random sampling employed supports the external validity of the study to a large extent. The internal validity of the study is supported by previous studies (i.e., Pesämaa et al., 2010) in which their measurements were adopted in this study. The report captures the issues of reliability and validity in the results chapter.

3.4 Design of Questionnaire

The study investigated the challenges of foreign investors in relation to networking and partnership. The constructs in the model are latent variables that cannot be observed directly. Therefore, a questionnaire was designed as a survey instrument. The questionnaire had different sections which included motives (loose and soft, hard), partner selection (expected goal congruence, network partner awareness), trust, reciprocity, performance and the biographical background information. The first five sections included major constructs of the study, which had closed questions. This section discusses the five major constructs of the study in detail, explaining the reasons for inclusion of certain variables. These constructs were developed based on the literature review in the field, including the theories. Each of the constructs and their inclusion are discussed in detailed below.

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3.5 Measurement of Variables

The relationship of the conceptualized constructs was measured using the questions on the questionnaire as follows:

1. Loose and soft motives were to be measured using two questions 1 and 2 2. hard explicit motives were to be measured using questions 3, 4 and 5 3. Expected goal congruence was to be measured using questions 6, 7 and 8 4. Network awareness was to be measured using questions 9-10 5. Trust was to be measured using questions 11, 12 and 13 6. Reciprocity was to be measured using questions 14, 15, 16 and 17 7. Performance was to be measured using questions 18, 19 and 20.

The variables were place in four categories A, B, C and D that formed the successive sections of the questionnaire. In section A, C and D which were about loose and soft- and hard explicit motives, trust, reciprocity and organizational performance respondents were asked to respond to each question or statement by marking the response alternative that best agrees with their own personal opinion: -3 = Strongly disagree, -2 = Somewhat disagree, -1= disagree, 0=Neither agree nor disagree (Neutral), 1 = Agree, 2 = Somewhat agree and 3 = Strongly agree. In section B respondents were asked to respond to each question or statement by marking the response alternative that best agrees with their own personal opinion. The scales ranged from: -3 = Unimportant , -2 = Somewhat unimportant, -1 = not important 0=Neither agree nor disagree (Neutral), +1 = important +2 = Quite important +3 = Very important. Details about operationalization of variables follow in the section 3.5.1-3.5.7 below.

3.5.1 Measurement of Loose and Soft Motives The relationship adapted by Pesämaa et al. (2010) posits that firms join networks based on specific motives and partner selection, and then adds commitment, taken from the work of Morgan and Hunt (1994), as an intermediating factor between the constructs given earlier and organizational performance. Two dimensions of motives were kept namely (1) Loose and soft motives (2) hard and explicit motives. The study by Pesämaa et al. (2010) found strong direct links of loose and soft motives to organizational performance rather than through commitment. Consequently this study adopted this construct of their model excepting of commitment. However, the findings may differ from those Ossi and others because the context of the study is a different context. For section A of the questionnaire, the measurement used was developed by Pesämaa et al. (2010). The questionnaire measured loose and soft motives using two (2) items: Loose and soft motive was operationalized using three variables:

Q1 to share information and to get connections Q2 to become more familiar with other business

3.5.2 Measurement of Hard Explicit Motives Still with section A and as with the previous construct, hard explicit motives was developed by Pesämaa et al. (2010) as one of the two factors that emerged from factor analysis in the study. This questionnaire measured hard explicit motives using three (3) items: Hard explicit motives was operationalized using three variables:

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Q3 sharing into new product developments Q4 to increase the ability to enter new geographical markets Q5 to increase the ability to enter new product segments

3.5.3 Measurement for Expected Goal Congruence The construct Expected goal congruence was developed from the model of Lundin (2007). In that study the questionnaire respondents were asked to grade, on a scale from one to five, the importance of 13 different objectives. The congruence between the ranking of a given public office and the municipality in each dyad was then calculated. Three factors similarity of goals, complementarity and strategic fit emerged from. These were adopted for section B of the questionnaire which measure Expected goal congruence using three (3) items. Expected goal congruence was operationalized using three variables:

Q6 select only those who share similar goals Q7 select those who have resources that I do not have Q8 select those with shared understanding of aims in a contract

3.5.4 Measurement of Network Awareness The construct network awareness was developed from Ritter et al. (2002) who carried out a study on network competence and its effect on organizational performance in terms of network centrality and dominance. Their study employed a twelve item scale that when subjected to factor analysis yielded two underlying factors that could be defined as self-knowledge of a company’s competence and fore-knowledge prospective partners competence. Network partner awareness, in section B of the questionnaire as well, was measured using two (2) items. Network awareness was operationalized by two (2) variables:

Q9 develop already established relationships Q10 select partners whose potential contribution I am aware of.

3.5.5 Measurement of Trust The construct trust was developed from the study by Pesämaa et al. (2010) which consisted of three items that tested the role of trust in achieving company performance. That study built on the work of Mavondo and Rodrigo (2001). As in Pesämaa et al. (2010) with this construct, respondents were asked in section C, to score three (3) items related to the partner being honest, confident, and trustworthy. Trust was operationalized using three (3) items Q11 partner(s) to be honest with me Q12 to have confidence in my partner Q13 my partner does not try to take advantage of my relationship

3.5.6 Measurement of Reciprocity The construct reciprocity was developed from the study by Pesämaa et al. (2010) too. That study employed three items that tested the role of reciprocity in achieving company performance and followed from the work of Mavondo and Rodrigo (2001). This study adopted the three items from Pesämaa et al. (2010) and added the variable Q14. “call in” favors any time as part of doing business with partners. Respondents were asked in section C, to score four (4) items. Reciprocity was operationalized using four variables: Q14 to “call in” favors any time as part of doing business with partners Q15 to practice “give and take” as part of being in relationships Q16 my partner(s) feel a sense of obligation for doing me favors

27

Q17 to return favors in doing business with partners.

3.5.7 Measurement of Performance The construct of organizational performance was based on the various researchers, for example Ellram (1990, 1991), Delaney and Huselid (1996), Spekman (1994), Das and Teng (2003) , Dickson (1966), Vickery et al. (1999), Stock, Greis and Kasarda (2000), Thanassoulis (1993), Devinney et al. (2009), Richard et al. (2009), Tippins and Sohi (2003), Richard et al. (2009), Vivek and Ravindran (2009), Moeller (2010). They used had varied approaches to measure the construct. Given the permutations of parametric and non-parametric measures of the construct, and in the interest of keeping the time to respond to questions short, three (3) items were selected from the possibilities to measure the construct based on the perception of the respondents. Organizational performance was operationalized using three (3) variables: Q18 increase sales Q19 have many new products Q20 have new customers

3.6 Ethical Considerations

In line with the applicable guidelines for ethical research in Trochim (2005), this study upheld the principles of voluntary participation, assurance of no harm, assurance of protection of privacy and subjection to a panel of persons who reviews grant proposals with respect to ethical implications, in this case the researcher’s supervisors under the Universities Code of Ethics. The research commenced on clearance by the School of Management of Blekinge Institute of Technology and in accordance with the MBA, IY2517 Course Guide. The researcher worked with data assistants from the Sudan Bureau of Statistics in order to be accountable to the mandated agency in charge of statistics in the country.

The study adhered to the principle of voluntary participation. No respondent was coerced into participating in research. Instead impromptu formal visits were made to selected organizations, an explanation of the purpose of the study given and permission requested to administer a questionnaire. The study fulfilled the requirement of informed consent by presenting the letter attached to the questionnaire and waiting for affirmation from the organizations’ managers who designated appropriate staffs to complete the questionnaires.

Ethical standards require that researchers not put respondents in a situation of risk of either physical or psychological harm as a result of their participation. The questionnaire language was checked for consonance with the cultural norms and values of people in the context. Questionnaires time-cost was kept low to avoid causing loss of employee-time of the companies. No respondent had to travel or spend money to complete the questionnaire. All costs to deliver and return the questionnaire were borne by the researcher.

Assurances were given to managers that the researcher would protect the privacy of the participating companies. They were assured that identifying information would not be made available to anyone who was not directly involved in the study. No respondent was required to give their name in line with the principle of anonymity.

28

Chapter 4: Empirical Findings and Analysis 4.1 Descriptive Results This thesis sampled a group of respondents that reflect the overall structure of South Sudan. 42.9 % of respondents were aged 18 to 40 years and the rest (57.1 % were older than 40 (Table 1)). There were relatively more male than female (136 to 48) respondents in this sample (Table 1). Approximately half of the sample (53.3 %) was CEOs while the rest were financial- or R&D managers (Table 1). Additionally there is a good representation of the three types of networking forms namely international networks, joint ventures and local networks (Table 1). The sample has a relatively good representation of the more financially demanding industry as well as industries that dominate South Sudan industry structure (Table 1). Finally the researcher captured a broad scope of investors from various countries (Table 1).

Table 1: Sample descriptive (N=184)

Cathegory Number of Respondents Percent Age 18-40 79 42.9 % Age>40 34 57.1 % Gender Male 136 73.9 % Female 48 26.1 % Position CEO 98 53.3 % Other, mostly financial or R&D managers 86 46.7 % Type of network International 59 32.1 % joint venture 24 13.0 % Local 101 54.9 % Type of industry Banking 11 6.0 % Telecom 3 1.6 % Construction 37 20.1 % Manufacturing 13 7.1 % IT 15 8.2 % Institution 9 4.9 % Others 95 51.6 % Nationality Tanzanian 4 2.2 % Swedish 1 .5 % Kenyan 32 17.4 % Others 147 79.9 %

4.2 Results of the Model This thesis reports how motives of networking related to expectations expressed by the way companies select partners and how these relationships have an effect on more expanded relationships such as trust and reciprocity. Finally these measures are related to how performance developed the recent years. The thesis has two different measures reflecting motives in which the first one reflects “loose and soft

29

motives” whereas the second one reflects “hard explicit motives”. The second part B of the theoretical idea is what companies expect from potential partners. This section reflects two different types of expectations. The first measure is “expected goal congruence” that a company wants to avoid partner interest does not match with that of the company. The second measure in partner selection is “network awareness” that reflects the fact that companies are already aware and knowledgeable about what the partners can be expected to perform. Finally, among the central parts of the model there is an actual performance measure reflecting sales, new products and new customers. In total there is 20 variables for these seven different theoretical constructs (see appendix).

4.2.1 Means, Standard Deviations and the Correlations Table 2 below describes means, standard deviations and the correlations among the 20 variables. The variables (Q1-Q20 in Table 2) below:

30

Tab

le 2

: Spe

arm

an c

orre

latio

n, M

eans

and

Sta

ndar

d D

evia

tion

(N=1

84)

M

ean

S.D

. Q

1 Q

2 Q

3 Q

4 Q

5 Q

6 Q

7 Q

8 Q

9 Q

10

Q11

Q

12

Q13

Q

14

Q15

Q

16

Q17

Q

18

Q19

Q

20

Q1

2.10

1.

07

1.00

Q2

1.38

1.

48

.55*

* 1.

00

Q3

1.89

1.

22

.08

-.03

1.00

Q4

2.21

1.

12

.15*

.0

8 .3

6**

1.00

Q5

1.62

1.

30

.19*

.2

4**

.34*

* .4

4**

1.00

Q6

2.00

1.

13

.07

.04

.21*

* .2

4**

.23*

* 1.

00

Q7

1.67

1.

49

.24*

* .3

0**

.04

.11

.29*

* .2

7**

1.00

Q8

2.05

1.

13

.14

.04

.32*

* .3

4**

.32*

* .4

8**

.36*

* 1.

00

Q9

2.10

1.

23

.05

-.03

.22*

* .4

3**

.24*

* .2

0**

.02

.39*

* 1.

00

Q10

2.

27

1.07

-.0

6 -.1

3 .2

4**

.24*

* .0

7 .3

7**

.06

.51*

* .5

2**

1.00

Q11

2.

76

0.58

.0

8 -.0

6 .1

1 .2

0**

.22*

* .1

2 .0

8 .2

0**

.15*

.0

6 1.

00

Q12

2.

74

0.58

-.0

0 -.1

2 .2

1**

.30*

* .1

9**

.18*

.0

9 .3

0**

.10

.13

.55*

* 1.

00

Q13

2.

08

1.37

-.1

0 -.2

1**

.25*

* .3

7**

.19*

.1

2 -.0

4 .3

2**

.46*

* .2

8**

.27*

* .3

8**

1.00

Q14

-0

.73

2.15

.2

9**

.56*

* -.1

7*

-.14

.06

-.13

.20*

* -.1

2 -.1

9**

-.26*

* -.1

6*

-.16*

-.3

0**

1.00

Q15

0.

14

2.10

.1

7*

.31*

* -.0

5 .1

0 .1

9*

.16*

.2

1**

.15*

.0

0 -.0

6 .0

4 -.0

1 -.1

0 .5

1**

1.00

Q16

-0

.84

2.06

.1

9**

.43*

* -.2

1**

-.08

.09

-.14

.04

-.12

-.16*

-.2

0**

-.22*

* -.1

1 -.2

8**

.66*

* .4

3**

1.00

Q17

-0

.80

2.14

.2

2**

.45*

* -.2

6**

-.21*

* .0

8 -.1

6*

.12

-.20*

* -.2

4**

-.31*

* -.1

2 -.1

7*

-.33*

* .6

8**

.43*

* .7

8**

1.00

Q18

1.

80

1.22

.3

1**

.40*

* -.0

9 -.0

4 .1

9**

.07

.29*

* .1

9**

-.04

-.01

.06

.06

-.28*

* .4

1**

.23*

* .3

7**

.40*

* 1.

00

Q19

1.

98

1.19

.1

5*

.11

.20*

* .4

5**

.42*

* .3

3**

.22*

* .4

2**

.33*

* .3

1**

.27*

* .4

4**

.23*

* -.1

1 .1

2 -.0

7 -.1

7*

.27*

* 1.

00

Q20

2.

02

1.07

.3

0**

.33*

* -.0

2 .1

3 .2

8**

.13

.30*

* .1

6*

.09

.05

.16*

.1

3 -.0

9 .3

4**

.33*

* .1

7*

.25*

* .6

0**

.37*

* 1.

00

Two

taile

d le

vel s

igni

fican

ce *

*p<.

01; *

p<.0

5; C

orre

latio

ns in

bol

d re

port

corr

elat

ions

with

in e

ach

fact

or.

31

4.2.2 Exploratory Factor Analysis Measurement is done to ensure that each of the constructs meet reasonable levels of measurement reliability. To confirm that these measures are reliable a discussion is followed by combining insights from correlation Table 1 and from an exploratory factor analysis (EFA). EFA reported in Table 3 reports output from a principal component analysis using Varimax solution and seven iterations. For the purpose of simplicity in reporting, Hair et al. (2010) signal that loadings with less than 0.50 indicate poor reliability. Consequently and for the purpose of simplicity, loadings with less than 0.50 were not reported by the SPSS data analysis program. Table 3: Exploratory Factor Analysis

Factor/ construct Loose and

soft motives

Hard and explicit motives

Expected goal

congruence Network

awareness Trust Reciprocity Performance Q1 .873 Q2 .739 Q3 .726

Q4 .583

Q5 .773

Q6 .787

Q7 .567

Q8 .722

Q9 .845

Q10 .615

Q11 .854

Q12 .882

Q13 .551

Q14 .797

Q15 .719 Q16 .885

Q17 .858

Q18 .695

Q19 .628

Q20 .842

Loose and Soft Motives First, the construct “loose and soft motives” is measured by two questions (Q1-2 in Table 2-3, refers to the appendix). These measures correlate substantially. This factor has substantial loadings that exceed recommended 0.50 suggested by Hair et al. (2010). As there are only two questions in this measurement (construct/ factor) there is no overall reliability coefficient Cronbach’s alpha reported about these correlations and factor loadings. Hard Explicit Motives Next (Q3-5 in Table 2-3, refer to the appendix) measure hard explicit motives. These measures correlate substantially within this factor (refer to Table 2). This factor has substantial loadings that exceed the recommended 0.50 suggested by Hair et al. (2010). Reliability coefficient Cronbach’s

32

alpha for these three questions is 0.60 which is marginally low but sufficient for exploratory analysis as Hair et al. (2010) recommend. Expected Goal Congruence Next (Q6-8 in Table 2-3, refer to the appendix) measure expected goal congruence. These measures correlate substantially within this factor (refer to Table 2). This factor has substantial loadings that exceed the recommended 0.50 suggested by Hair et al. (2010). Reliability coefficient Cronbach’s alpha for these three questions is 0.62 which is marginally low but sufficient for exploratory analysis as Hair et al. (2010) recommend this to exceed 0.60 for exploratory purposes. Network Awareness Next (Q9-10 in Table 2-3, refer to the appendix) measure expected network awareness. These measures correlate substantially. This factor too has substantial loadings that exceed the recommended 0.50 suggested by Hair et al. (2010). As there is only two questions in this measurement (construct/ factor) there is no overall reliability coefficient Cronbach’s alpha reported but these correlations and factor loadings. Trust Next (Q11-13 in Table 2-3, refer to the appendix) measure trust. These measures correlate substantially. This factor as well has substantial loadings that exceed the recommended 0.50 suggested by Hair et al. (2010). This factor has substantial loadings that exceed recommended 0.50 suggested by Hair et al. (2010). Reliability coefficient Cronbach’s alpha for these three questions is 0.57 which is marginally low, which impacts their reliability. Reciprocity Next (Q14-17 in Table 2-3, refer to the appendix) measure reciprocity. These measures correlate substantially. This factor has substantial loadings that exceed the recommended 0.50 suggested by Hair et al. (2010). Reliability coefficient Cronbach’s alpha for these three questions is 0.82. Hair et al. (2010) recommend this to exceed 0.70 for explanatory purposes. Performance Next (Q18-20 in Table 2-3, refer to the appendix) measure performance. These measures correlate substantially. This factor has substantial loadings that exceed the recommended 0.50 suggested by Hair et al. (2010). Reliability coefficient Cronbach’s alpha for these three questions is 0.65 which is marginally low but sufficient for exploratory analysis as Hair et al. (2010) recommend this to exceed 0.60 for exploratory purposes.

4.3 Test of Hypothesis To test hypothesis the constructs are tested in a regression. The first test is carried out based on a model (Model 1) with motives that are expected to have a significant effect on performance. In the second model (Model 2 in Table 4) the two partner selection factors/ constructs are introduced into the model. Consequently there is a check to determine if these have effect on performance and whether the coefficient of motives changes as these addition variable enter the model. In third model (Model 3 in Table 4) trust and reciprocity are introduced into the model and again there is a check to determine if these variables too relate significantly to performance, and if coefficients of motives or partner selection changes as a result of their entry.

33

Table 4: Stepwise regression

Model 1 Model 2 Model 3 Beta p-value Beta p-value Beta p-value H1: Soft motives --> performance ,256 ,000 ,218 ,002 ,126 ,098

H2: hard explicit motives --> performance

,213 ,003 ,127 ,083 ,138 ,063

H3: Goal congruence --> performance ,228 ,002 ,213 ,004 H4: Network awareness --> performance

,076 ,290 ,115 ,111

H5: Trust --> performance ,035 ,630 H6: Reciprocity --> performance ,217 ,005

R2 Performance 12.6 % 18.3 % 21.8 % Adj R2 performance 11.6 % 16.5 % 19.1 % Firstly, by looking at ad R- square (Table 4) the models explain 11.6 to 19.1 % of variance in performance. Secondly, H1 (Table 4) predicted that loose and soft motives have a significant relationship on performance. This prediction is confirmed as (β=.26; p-value<.000). H1 is thus supported and as the p-value similarly decreases in model 2-3 it is likely as well that these effects get stronger by accurate partner selection and expanding relationships using trust and reciprocity. Thirdly, H2 predicted that hard explicit motives have a significant relationship on performance. This prediction is confirmed since (β=.21; p-value<.05). H2 is therefore supported. The decrease of the p-value in model 2 indicates that this particular motive is strengthened by accurate partner selection. However since it goes down in Model 3 when trust and reciprocity enter model, it is not necessarily true that the benefit of this kind motives depends on these expanded relationships. Fourth, H3 (see Table 4) predicted that goal congruence has a significant relationship on performance. This prediction is confirmed as (β=.23; p-value<.05). H3 is thus supported. The p-value decreases in model 3 so it is likely that these effects get stronger by expanding relationships with trust and reciprocal relationships (see Model 4 in Table 4). Fifth, H4 predicted that network awareness has a significant relationship on performance. However, this is not true as (β=.08; p-value>.10) beta is weak and insignificant. Sixth, H5 predicted that (Model 3 in Table 4) trust has a significant effect on performance. However this was found to be false. Trust has only an insignificant effect on performance (β=.04; p-value>.10). Finally, H6 predicted that (Model 3 in Table 4) reciprocity has an effect on performance. This prediction is confirmed as (β=.23; p-value<.05).

4.4 Validity and Reliability

According to Pesämaa et al. (2010)

“Convergent validity is the extent to which the individual items in a construct share variance between them (Hair et al., 2006). Nomological validity means that the direction of the relationships is consistent with theory. The correlations are positive, indicating that the results are consistent with theory and confirming nomological validity (see Table 2). Discriminant

34

validity examines whether the constructs are measuring different concepts (Hair et al., 2006).” (p. 72-73).

85% of the correlations between measures are positive, indicating that the results are largely consistent with theory and confirming nomological validity (see Table 4). Convergent and discriminant validity were confirmed in Pesämaa et al. (2010). Table 5: Internal reliability of the instrument Number of Items Construct Cronbach’s alpha Internal reliability

2 Loose and Soft Motives - none overall 3 Hard Explicit Motives 0.60 marginally low 3 Expected Goal Congruence 0.62 marginally low 2 Network Awareness - none overall 3 Trust 0.57 marginally low 3 Reciprocity 0.70 acceptable 3 Performance 0.65 marginally low

Table 5 summarizes, by construct, the internal reliability of the instrument used item by item. In two constructs, loose and soft motives and network awareness, there is no overall reliability calculated since not more than two questions per item were asked. In four constructs hard explicit motives, expected goal congruence, trust and performance, internal consistency is marginally low. Reciprocity on the other hand had acceptable internal consistency. Overall the internal consistency of the instrument used sufficed for exploratory purposes.

35

Chapter 5: Discussion

5.1 Lessons Earlier theory postulated that relationships in networks tend to have an effect on performance (Pesämaa et al., 2010). Earlier theory similarly postulated that these grow in sequences beginning from motive and partner selection on performance (Pesämaa et al., 2010). Pesämaa et al. (2010) applied both loose and soft and hard explicit motives in their model tested in the U.S. This thesis is in congruence with these findings but differs in that it represents a different context, South Sudan. The finding that models in this study demonstrated that 11.6 to 19.1 % of variance in performance of companies in interorganizational networks in South Sudan as (see R- square (Table 4)) suggest that there other factors that influence organizational performance but are yet to be studied. Such factors might include attitude of client towards companies, national culture, the legal framework for business in South Sudan and the geo-political landscape. This interplay of these factors with the factors in the model and their effect on performance will require further examination in future studies. Secondly, H1 (Table 4) predicted that loose and soft motives have a significant relationship on performance. This prediction is confirmed as (β=.26; p-value<.000). H1 is thus supported and as the p-value decreases as well in model 2-3 it too is likely that these effects get stronger by accurate partner selection and expanding relationships using trust and reciprocity. First, H1 and H2 related to loose and soft- and hard explicit motives respectively are similar to findings of Pesämaa et al. (2010). They have an effect on performance that becomes stronger when there is accurate partner selection and further when relationships are expanded by trust and reciprocity. This shows that loose and soft- and hard explicit motives have strategic value as demonstrated by this study. This suggests that companies investing in Sudan are cognizant of their strategic goals in terms of organizational learning and resource accumulation with the aim of achieving dominance in their sphere of influence. New companies can emulate this example and invest with goal clarity if they would achieve their organizational goals as part of interorganizational networks. It follows that since loose and soft- and hard explicit motives are birthed and clarified in human minds before being written down, companies need to invest in idea generation from their employees. The ideas should then be sifted by a team of innovators into the plans that drive the agenda of interorganizational networking in their favor. Similarly and in accordance with earlier studies (Pesämaa et al., 2010) partner selection too affects performance. Partner selection was represented by expected goal congruence and network awareness represented by hypotheses H3 and H4 respectively (Ellram 1990, 1991; Child and Faulkner, 1998; Dekker, 2008; Moeller, 2010). They too have an effect on performance but dilute the effect of trust when the relationship is expanded by trust and reciprocity. In line with organization control over motives, the study suggests that companies in South Sudan demonstrate both expected goal congruence and network awareness. This is in line with previous studies (ibid.) and clarifies the importance of these factors South Sudan. Existing companies and new companies need to engage each other on business strategy to better understand and utilize their points of agreement while downplaying their differences. Goals are motives as well and if they are incongruent the efforts of cooperating companies are thwarted and organizational performance falls. The study demonstrates that companies in South Sudan value network awareness as they do motives. It follows that other companies planning to invest in Sudan ought to know what companies exist in their business environment with whom they can or cannot cooperate. They have to update their knowledge of existing and potential partners and their business practices continuously. Third it is surprising that trust represented by H5 does not matter in South Sudan. This is unlike what the theory predicted would be as found by Lundin (2007); Miller (1992), Pesämaa et al. (2010). Seeing

36

as trust is the reliance by one company on another entity based on the other entity’s honor, it would appear that companies in South Sudan do not attach value to honor alone. It could be explained by the nascence of the economy in which companies are not sufficiently conversant with companies that they have not worked with and as such do not trust them in the course of doing business together except in the framework of contracts and close supervision. Since trust is the expectation that an exchange partner will not engage in opportunistic behavior (Chiles & McMackin, 1996), it may be that such a phenomenon is driven by past experiences in which one or more partners in a cooperation agreement turned opportunistic at the expense of their partner leading to dispensing with trust in future relations. Alternatively the situation may be an indicator of the perceived threat of extinction of a business with in South Sudan when trust is breached. Companies refrain from dealings which pose a threat if they have to rely on pure trust alone in preference for opportunities that guarantee a return of value however small. On the other hand reciprocity represented by H6 matters and affects organizational performance as predicted in the literature (Burt, 1992; Mohr and Spekman, 1994; Meuleman et al., 2010; Chung, Singh & Lee, 2000; Vivek & Ravindran 2009; Pesämaa et al., 2010). This result confirms that reciprocity is a compelling factor that results in mutual or cooperative interchange of favors or privileges between organizations in South Sudan. It signifies that companies that plan to do business in South Sudan have to be ready to respond to positive actions from other companies with positive action themselves (Pesämaa et al., 2008). Reciprocity in South Sudan makes business sense since another company avails, at no cost, resources such as references, information about inputs, staff expertise and market for goods that create value for a different firm. Consequently an obligation is created to reciprocate and return the favors with similar or different resources such as discounts, free conference facilities, business advice and interest-free loans. Companies planning to invest in South Sudan need to invest in this transactional reciprocity more so in organizational networks. This thesis sampled a group of respondents that reflect the overall structure of South Sudan. 42.9 % of respondents were aged 18 to 40 years and the rest (57.1 % were older than 40 (Table 1). This demonstrates that a significant number of influential decision makers (CEOs while the rest were financial- or R&D managers) are youthful, a demographic indicator that may be useful for businesses that target youthful entrepreneur managers for interorganizational networking and for accessing market niches of the younger population. The disproportionate distribution of genders (136 male to 48 female) among the respondents signifies that the interorganizational network setting may be a male-dominated domain in which women find it hard to rise to the ranks of organizational leadership in South Sudan. It definitely shows that the majority of decision makers are males. It may represent the difficulties female executives may encounter compared with males in running businesses under interorganizational networking in South Sudan. The good representation of the three types of networking forms namely international networks, joint ventures and local networks reveals the potential for the formations, existence and viability of interorganizational networks both now and in the future. The findings of the study can be regarded as a true representation of the companies in the population of companies in South Sudan. This is indicative of the effects of loose and soft- and hard explicit motives, reciprocity, network awareness and expected goal congruence driving the performance of the cooperating companies involved. The relatively good representation of the more financially demanding industry as well as industries that dominate South Sudan industry structure shows that the opportunity for companies to invest in the country through interfirm collaboration is extensive and the basic industrial backbone for successful running of complementary business is already in place. This is in line with the hard explicit motive of the companies involved. The broad scope of investors from various countries (Table 1) is indicative of the high interest that international companies with know-how, experience and an exploratory agenda have taken in South

37

Sudan. The nationals from different countries are most likely drawn by the large number of highly profitable ventures that they can engage in and the existence of companies with whom the network to achieve their goals. This too is in line with the Hard Explicit Motive of the companies involved.

38

Chapter 6: Conclusions and Recommendations This study asked What effect does social capital capitalized from partner goals, selection and motive have on organizational performance? The study sought to understand how risk management influences organizational performance in South Sudan. The study investigated the challenges of foreign investors in relation to networking and partnership. The objectives of the study were to explain and propose a testable theoretical model to explain of network relationships and its correspondence on company performance in South Sudan. Specifically, the research objectives were to:

1. Test the effect of initial motives on performance 2. Examine the effect of criteria of selecting a partner on performance 3. Assess the influence of trust on performance 4. Test the influence of reciprocity on performance

In this study the focus was on issues related to market operations such as creating and keeping customers to local and global markets and related risks and uncertainties arising to investors and companies.

6.1 Contributions of the Study This study has contributed to the response to the main problem of lack of researched studies in interorganizational cooperation with in South Sudan. The study has blazed the trail for further study on the topic of interorganizational cooperation in the country. The specific contribution of the study is that it has confirmed, in line with previous studies in other contexts that a relationship exists between loose and soft motives and hard explicit motives; reciprocity; partner’s selection represented by expected goal congruence and network awareness, and organizational performance within the context of interorganizational networks.in the Republic of South Sudan. The study has contributed to obtaining evidence of how these outcomes occur within this setting. Companies in South Sudan now have the findings of an exploratory study to guide their business decisions concerning value-adding relationships with other companies. It is no longer the preserve of only the companies in existing cooperating relationships to benefit learning and harnessing the benefits of cooperation from their experiences. Others companies that wish to engage in interfirm relationships can now have a rationale for doing so. International companies no longer have to rely on guesswork, hearsay and subjective reports to make cooperation-based investment decisions in South Sudan. In this study in the Republic of South Sudan the researcher has contributed to shedding light on this subject. The study has extended theoretical models posited by Parkhe (1993) and developed Pesämaa et al. (2010) by testing it without intervening interorganizational commitment that was found to affect organizational performance too but did not mediate sufficiently the study variables. Furthermore the study has introduced the dimension of a third world country, testing the model to incrementally contribute to its external validity. The study has uncovered a surprising result that, to a reasonable extent, the organizational performance of companies in interorganizational relationships in South Sudan is not driven by trust as an enduring basis for forming and operating interorganizational networks. As such, foreign-owned companies that originate from outside the context may need to rely on legally enforceable agreements and close monitoring to ensure the achievement of organizational goals with in South Sudan. If such companies already have existing partner companies on the ground or a transitive relationship to local

39

through other companies networking with them, then it may be practical to form interorganizational arrangements to pursue their mutual goals.

6.2 Implications The main implications of this study is that companies in South Sudan and possibly companies elsewhere that are involved in interorganizational networking now or want to do so in the future would first need to invest resources of time and money in clarifying their hard explicit motives. The mix of hard explicit motives would need to be realistic and take into account the effect of the expressed hard explicit motives on the local partner companies in Sudan. Achievable motives that do not alienate the network partners will most likely lead to good organizational performance. Secondly, the loose and soft motives of companies that engage interorganizational networking in South Sudan and probably in other settings need to be regarded as opportunities to gain strategic value and therefore require deliberate investment of time and effort. Organizations that adopt the approach of learning from their network partners and applying what they learn in business will experience good organizational performance. Thirdly, companies in South Sudan and may be in other places, that would succeed in their performance may have to select partners carefully with the view of matching their mutual goals, a combination that has been demonstrated to boost company performance. They may need to select or drop partners according to the existing and emerging goals of each so as to minimize the chance of their network collapsing along with their investment in it. Fourth, new companies wishing to network in South Sudan may need to invest in network partner awareness and keep a database of potential partners with whom to network. The knowledge is necessary for starting relationship and starting off with the right relations guarantees organizational success while a poor choice would most likely result in failure. Fifth, companies wishing cooperate with other companies to invest in South Sudan based on pure trust alone should not hope to attain reasonable change in organizational performance as trust in this setting is downplayed in preference for monitoring, contracts and commitments that are legally enforceable. Trust may have its place at later stages when companies have cooperated for long and the partners learn to dispense with stringent legal requirements. Sixth, companies that wish to have excellent performance under interorganizational networking ought to learn and practice reciprocation, doing good turns for good turns, returning favors, matching the generosity and magnanimity of their partners through gestures that add value to them. This will ensure that resources are exchanged equitably and value-creation results in larger productivity from the synergy of reciprocating efforts. The companies must learn to be givers in order to get what they need.

6.3 Limitations and Future Research

The anticipated limitations to the study are that it is based on a one time measurement of effect in a single country, and it relies on subjective reports of organizational performance to study relationships between constructs. Attempts to generalize the findings ought to be done with care.

The study did not make a distinction between cooperation involving dyadic relations only and other relationships with greater numbers of participants (Sydow, 2003, Moeller, 2011). As such the fine interplay of the constructs studied may not be clear from this study and may require further examination by disaggregating interorganizational networking and cooperation. Future studies could study the influence of such factors as the attitude of client towards companies, national culture, the legal framework for business in South Sudan and the geo-political landscape on the factors in the model of this study.

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Viewed from another angle, motives may require adaptation to changing circumstances and emerging issues. South Sudan being a new country is in a period of transition in which companies need to adapt their motives if they are to survive. The study analyzed motives but did not investigate whether and how motives were modified when South Sudan was declared an independent state. As such it may be that the change in motives itself had an effect on the current performance of the firms but this will require further study.

The perceptions about trust in doing business in South Sudan require a follow up study to better assess whether trust not having an effect on organizational performance is a temporary or permanent feature in the economy. Further the study should explore whether it is the relationship between trust and other factors such as ethnicity, stereotypes, gender or age that have an effect on organizational performance.

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Appendix

QUESTIONNAIRE FOR INVESTORS

Dear Ms/Mr, All enterprises belong to some networks consisting of other enterprises, customers, subcontractors, bankers, their community contacts, families etc. They all have some stake in the companies. Therefore they are called stakeholders. Many companies work with external investors and other partners to raise capital and to obtain financing. They hope to manage and share risks, increase customer knowledge, gain access to a selected markets or search for some other source of value. Herein we refer to such external persons or organizations as “partners”. They benefit the company by investments that may be in terms of money invested, knowledge shared or some other important resource enhancing company operations. In this research project we seek to better understand the challenges of South Sudanese companies related to cooperation and networking. Specifically, we focus on issues related to market operations such as creating and keeping customers in local to global markets, and related risks and uncertainties arising to investors. What are the company´s risks (think in terms of static, dynamic, inherent or speculative risks) when investing in different destinations? Answers to these questions will enable you as a member of this network to possibly become more successful in managing risks. These issues and questions are in foci of a major comparative research agenda carried out in several countries including Africa, Asia and Europe. Insights gained may also help you as a member of the cooperating destination network. This survey takes about 5-7 minutes to fill out. Most of the questions are standardized and can be filled out very quickly by just sharing your opinion. The result will be presented in local and regional business papers and other information sources, Chamber of Commerce and other meetings, in international conferences and eventually in academic journals. These sources of image building will also render your region good-will over a long time. Thank you, already in beforehand for your contribution in participating in this research activity.

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PART A.

This part of the survey addresses initial motives before establishing a relationship with a new partner. (Please respond to each question or statement by X-ing the response alternative that best agrees with your own personal opinion). The scale ranges from -3 = Strongly disagree to +3 = Strongly agree

A. Before entering a partnership, how well do the following initialmotives reflect the need to enter a relationship with a new partner . . . -3 -2 -1 0 +1 +2 +3 Loose and soft motives 1) to share information and to get connections 2) to become more familiar with other businesses Hard and explicit motives 3) sharing into new product development costs 4) to increase the ability to enter new geographical markets 5) to increase the ability to enter new product segments

PART B. Often we call the first meeting the moment of truth, when a relationship is about to be created and contracted. Please determine the relevant criteria when you select a new business partner. (Please respond to each question or statement by X-ing the response alternative that best agrees with your own personal opinion). The scale ranges from -3 = Strongly disagree to +3 = Strongly agree

B. Main criteria for selecting a partner reflects my wish to . . . -3 -2 -1 0 +1 +2 +3 Expected goal congruence 6) select only those who share similar goals 7) select those who have resources that I do not have 8) select those with shared understanding of aims in a contract Network partner awareness 9) develop already established relationships 10) select partners that I am aware of their potential contribution.

PART C. As you are in a formal or social contract, please assess your relationship orientations towards a new partner with regards to your organization's performance? (In the following sections (3-5) please mark an X by the response alternative that best corresponds to your opinion). The scales range from -3 = Unimportant to +3 = Very important

C1. In considering trust, I always expect . . . -3 -2 -1 0 +1

+2 +3

11) partner(s) to be honest with me 12) to have confidence in my partner 13) my partner do not try to take advantage of my relationship

C2. In considering reciprocity, I always expect. . . -3 -2 -1 0 +1

+2 +3

14) to “call in” favors any time as part of doing business with partners

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15) to practice “give and take” as part of being in relationships 16) my partner(s) feel a sense of obligation for doing me favors 17) to return favors in doing business with partners.

PART D. Please assess the extent you agree on following aspects of partnering for your organizational performance? In this section, please mark by an X the response that best corresponds to your own business.

The scales range from -3 = Strongly disagree to +3 = Strongly agree D. In considering influences of partnering from the viewpoint of performance it significantly helped us over the last year/years to . . . -3 -2 -1 0

+1

+2 +3

18) increase sales 19) have many new products 20) have new customers

PART E. Please respond to the following questions about yourself and your organization.

Age _____ years Gender male female

Position (e.g., CEO, Financial manager, R & D manager)

___________ Company/Firm ownership status

International

Joint venture Local

Nature of employment (e.g., permanent, temporary)

___________ Location (region) __________

Nationality (e.g., South Sudanese, Swedish, etc.)

___________

Company size (number of employees)

__________

Experience working with the company (years/months)

___________ Company existence (age) in South Sudan (year/months)

__________

Source of Finance

Loan

Private

Have you invested in same business/es outside South Sudan? Where?

___________

___________

THANK YOU FOR YOUR TIME AND PARTICIPATION