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e-Informatica Software Engineering Journal, Volume 12, Issue 1, 2018, pages: 265–302, DOI 10.5277/e-Inf180111

A Literature Review on the Effectivenessand Efficiency of Business Modeling

Magnus Wilson∗, Krzysztof Wnuk∗, Johan Silvander∗, Tony Gorschek∗

∗Faculty of Software Engineering, Blekinge Tekniska Högskola, Karlskrona, [email protected], [email protected], [email protected], [email protected]

AbstractBackground: Achieving and maintaining a strategic competitive advantage through businessand technology innovation via continually improving effectiveness and efficiency of the operationsare the critical survival factors for software-intensive product development companies. Thesecompanies invest in business modeling and tool support for integrating business models into theirproduct development, but remain uncertain, if such investments generate desired results.Aim: This study explores the effects of business modeling on effectiveness and efficiency forcompanies developing software-intensive products.Method: We conducted a systematic literature review using the snowballing methodology, fol-lowed by thematic and narrative analysis. 57 papers were selected for analysis and synthesis, afterscreening 16 320 papers from multiple research fields.Results: We analyzed the literature based on purpose, benefit, challenge, effectiveness, andefficiency with software and software-intensive products as the unit of analysis. The alignmentbetween strategy and execution is the primary challenge, and we found no evidence that businessmodeling increases effectiveness and efficiency for a company. Any outcome variations may simplybe a result of fluctuating contextual or environmental factors rather than the application ofa specific business modeling method. Therefore, we argue that governance is the fundamentalchallenge needed for business modeling, as it must efficiently support simultaneous experimentationwith products and business models while turning experiences into knowledge.Conclusion: We propose a conceptual governance model for exploring the effectiveness andefficiency of business modeling to occupy the missing link between business strategy, processes andsoftware tools. We also recommend managers to introduce a systematic approach for experimenta-tion and organizational learning, collaboration, and value co-creation.

Keywords: business modeling, business model operationalization, effectiveness, efficiency,context-dependent, governance, software-intensive product development, literature review

1. Introduction

Software-intensive product development (SIPD)companies experience digitalization of their busi-ness environments. The embedded flexibility thatsoftware offers merges with the high-pace tech-nology innovation, resulting in new business op-portunities for creating and capturing value indigital business ecosystems [1, 2]. This has impli-cations for the business model.

A business model is a blueprint for a com-pany’s business logic and a description how to

manage and innovate the business. Central toa business model is how an organization cre-ates, delivers, and captures value [3]. Businessmodels can be seen as a set of choices and conse-quences of these choices (strategies and tactics)that impact the realizing organizations, businessprocesses, products, and systems [4]. Businessmodeling in a business ecosystem is an activitybased on transactions of activities geared towardvalue creation for all stakeholders [5]. Businessmodeling (BM) is also a practice that aims toanalyze the business environment and acquire

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266 Magnus Wilson et al.

insights to formulate and drive change, by adapt-ing and aligning the business strategy with theexecution to ensure value delivery for all stake-holders [6, 7].

Optimizing value creation requires profoundunderstanding how the implemented businessmodel (organization, business processes, and sys-tems) interacts with products and stakeholdersfor value creation and value capture [8]. SIPDcompanies have a unique position for optimally(efficiently) creating the correct (effective) valuefor all stakeholders. Given that software is themain component in: 1) the tools for implementingand supporting core business processes; 2) de-veloping the software product itself, and 3) inte-grating the product into the business ecosystem,SIPD companies could seamlessly adapt and in-tegrate their products to their business modelusing business modeling [9].

The business model mediates the link be-tween technology and a company’s performance,but the literature is missing the studies whichfocus on the interdependencies between businessmodel choice, technology innovation, and success[10], as well as differentiating the value creationand value capture analysis over individual, or-ganization, and society level [8]. Several promi-nent authors emphasized the lack of coherenceand clear focus in the business model literature[7, 11,12]. In particular, there is a gap in under-standing how BM interacts with software-inten-sive products in the digitalization transformation,and what effects BM have on increasing the ef-fectiveness and efficiency of the SIPD companiesand maximizing the technology innovation real-ization effects.

This literature study aims to address this gapby investigating what factors determine the effec-tiveness of BM, and if BM can act as an enablerfor improvements in effectiveness and efficiencyof SIPD companies. This study provides a soft-ware engineering perspective on how softwareand software-products enable value creation asthe unit of analysis for BM. This perspective en-ables us to narrow the scope of the vast businessmodel literature, as well as limiting the size ofthe study by defining a more precise context foranalyzing effectiveness and efficiency, as affected

by the on-going digital business transformation.Based on the literature review results, we presenta summary of benefits and challenges associatedwith BM including reported impacts on the ef-fectiveness and efficiency of the business. Next,we synthesize the implications for the researchand practice of BM and propose a conceptualgovernance model (CGM) for exploring the effec-tiveness and efficiency of BM (addressing boththe innovation of business models as well as theoutcome on company level for the implementedbusiness model).

The paper is structured as follows. In Sec-tion 2, we introduce fundamental concepts re-lated to BM and theories used to investigate themultifaceted, cross-disciplinary view of BM andbusiness models. Section 3 reports on relatedwork to BM and its usefulness while Section 4contains a detailed description of the study de-sign and study execution including a validity dis-cussion. Results are presented in Section 5, start-ing with general results around the study itself,followed by the detailed results regarding eachresearch question. In Section 6, our research syn-thesis including trends and our proposed CGMfor exploring BM are presented. Finally, in Sec-tion 7, we list six implications for researchersand industry followed by our conclusions andkey statements in Section 8.

2. Background

2.1. Effectiveness, efficiency, andgovernance in BM context

Business modeling shares several similarities withsoftware engineering, requirement engineering [13–15], and software product lines (SPL) [16]. Soft-ware engineering provides new possibilities to effi-ciently and effectively implement strategies agreedupon during business modeling activities [2].

The business model literature describes sev-eral concepts associated with effectiveness andefficiency. They are often adapted to specificcontexts, e.g., organizational efficiency, manufac-turing efficiency, operational efficiency, productdevelopment efficiency, and expressed as a value,

A Literature Review on the Effectiveness and Efficiency of Business Modeling 267

time or in financial terms as for costs, revenues,profits, and margins. By starting with an “um-brella definition” offered by Webster-Merriamon-line, we will discuss definitions suitable forSIPD companies and our study.

Effectiveness is the power to produce the de-sired result. Efficiency is defined as the abilityto do something or produce something withoutwasting materials, time, or energy: the quality ordegree of being efficient (technical), but also as thepower to produce the desired result causing someambiguity between the two terms. Buder et al.differentiate between quality (effectiveness) andrequired effort (efficiency) [17]. Organizationaleffectiveness is discussed by Zheng et al. in combi-nation with strategy and knowledge management,where they use the definition the degree to whichan organization realizes its goals [18].

Effectiveness is often measured as the qualityof the desired result and Frökjeaer et al., in theirattempt to correlate usability to efficiency andeffectiveness, they define efficiency as [. . . ] is therelation between (1) the accuracy and complete-ness with which users achieve certain goals and(2) the resources expended in achieving them [19].Measurements of efficiency are often related (di-rect and indirect) to time and cost. In economicsthe term efficiency focus on different aspects ofthe balance between supply and demand. It ismeasured by the relationship between the valueof ends and the value of means and examples ofterms are allocative efficiency (production repre-sents customer preferences) and productive effi-ciency (cannot produce more of one good withoutsacrificing production of another).

Effectiveness and efficiency are subjectiveand depend on evaluations. Such evaluationsare based on an individual’s understanding ofknowledge and interpretation in a specific con-text [20]. Therefore, having the same understand-ing of a context (which the measurements arerelative to), is fundamental when defining ef-fectiveness and efficiency measurements for BM(and the over-arching business context). Currentresearch on context description in software en-gineering provides a useful checklist on contextfacets (product, processes, people, practices andtechniques, and organization and market) [21].

Understanding, specifying, and sharing contex-tual factors (often as part of contractual agree-ments) is a critical factor for systematically opti-mizing the level of sub-optimization in a businessecosystem.

Effectiveness and efficiency are also closelyrelated to governance, and Webster-Merriamon-line defines governance as the way that a city,company, etc., is controlled by the people who runit. Understanding governance is also a crucialpart of BM as indicated by for example [5,22,23].Jansen considers measurements and governanceas the enablers of a successful software ecosys-tem [24]. Zott and Amit argue governance isa vital part of evaluating BM experimentation[5]. Page and Spira discuss corporate governanceconnected to the business model as a growingneed to attain accountability by the board byconsidering conformance, performance, and over-seeing management control systems. They con-clude that corporate governance is essentially thesame thing as sustaining and developing busi-ness models [25]. In this paper, we will use theWebster-Merriam definition of governance.

2.2. Business modeling as an enablerfor a company’s efficiency andeffectiveness

There are many diverse and even divergentdefinitions of a business model and BM, asalso highlighted in many literature reviews, e.g.,[7,11,12,26]. A business model “models the busi-ness”, but as such it has a wide range of usagedepending on who and why is using it. It canbe used as a description of “kinds and types”in a taxonomy to compare businesses or likea recipe for designing and innovating successful(new) business. Business models can also act asa description of the “logic of the firm”, i.e., howto create value and generate profit, or as a scalemodel to investigate, analyze, and evaluate dif-ferent strategies and tactics, thereby supportingboth strategic and daily decision making [27].

There are two ways to interpret “efficientand effective.” One interpretation is that the BMprocess itself should be efficient and effective.The other interpretation is that the business


model realization should increase a company’sefficiency and effectiveness, i.e., BM should bethe practice that increases a company’s efficiencyand effectiveness. In this work, we follow the sec-ond interpretation of efficient and effective, aswe are primarily interested in BM as a way toenable improvements in a company’s efficiencyand effectiveness. Therefore, we base our workon the BM definition by Rohrbeck et al. as tobe a creative and inventive activity that involvesexperimenting with content, structure, and gover-nance of transactions that are designed to createand capture value [28]. This definition supportsour investigation of BM for SIPD companies intwo ways. Firstly, looking at value creation trans-actions allows for a value-driven business modelanalysis in a business ecosystem. Secondly, byintroducing the word experimenting, it extendsBM to a process of “translating an idea intoexecution, testing and changing until satisfied,”similar to the agile software development meth-ods. We complement the BM definition with theproposed capabilities needed for BM (understandand share, analyze, manage, and prospect) [9].

2.3. Translating business strategy intoexecution using business models

Casadesus-Masanell & Ricart argue a clear dis-tinction between strategy and the business model,where the business model is a reflection of thefirm’s realized strategy and that the strategy isthe plan and process to reach the desired goal, viathe business model and onto tactics [4]. Amongthe authors that recognize the role of the busi-ness model in translating business strategy intoexecution, Doganova talks about the businessmodel as a “calculative and narrative device” toinnovate and translate the business strategy intoexecution [29]. In the same vein, Osterwalderdefines the business model as a formal model tocapture and translate a value-based business ideainto requirements for the ICT systems and the or-ganizations that execute that business model [9].Höflinger defines A business model is the designof organizational structures for converting tech-nological potentials into economically valuableoutputs by exploiting business opportunities [7].

For this paper, we combine our transaction-based(bottom-up) definition of BM with Höflinger’s(top-down) framework for defining the businessmodel since:– He extensively integrates and builds on the

literature for business models.– He addresses the issue of static versus dy-

namic business models (where he supports thestatic nature of the business model and arguesbusiness model innovation as the approachto adapt to rapidly changing environments).

– He focuses on the consequences regardingmulti-value, superior performance and organi-zational learning as a mechanism for feedbackand control.

– By taking an inside-out view of the researchgap addressed in this study, i.e., based onhow software and software-products enablevalue creation as the unit of analysis for BM,it enables both a top-down and bottom-upanalysis.Translating business strategy into execution

is not an easy task and requires experimentationwith content, structure, and governance of trans-actions that are designed to create and capturevalue [28]. Rohrbeck et al. advocate collabora-tive BM as a way to deal with the complexityand uncertainty of systems and markets. Theystress the need for planning, decision making, val-idation, and experimentation in highly complexenvironments. Other scholars also acknowledgedthe role of experimentation in BM [30–32]. Ex-perimentation can help to capture and managethe business environment dynamics, but it alsoimplies new challenges in addition to just cap-turing and designing a business model. Some ofthese challenges are emphasized by Ballon whenhe argues it is precisely the alignment of controland value parameters that is of most relevance tobusiness modeling in his aim to describe a theoret-ical foundation for operationalization (preparingfor execution) of the business model [33]. Ballonproposes an analytical framework for making thescope for choice explicit while connecting valueto the configuration of a business model, whileothers formulate the main challenge as organi-zations have to reach the alignment state andmaintain it alongside its evolution [34].


2.4. Capturing the change dynamicsand value with software products

Effectively dealing with change requires under-standing how the concept of strategy relates tothe business model and tactics [4], what strate-gic agility [35] and strategic flexibility [36] theorganizations have, as well as how changeability(adaptability, agility, robustness, and flexibility)can be operationalized using modularity in designand software-based systems [37]. Flexibility andadaptability has since long been a top priorityfor CEOs1 and business model innovation is be-coming a top priority amongst CEOs2. Hence, animportant part of analyzing efficient and effectiveBM translates to capturing and managing thechange dynamics of today’s business operations.

Value creation and value capture are the cen-tral concepts for BM. However, there is stillmissing consensus on the boundaries of theseconcepts, based on: (1) plurality in source andtarget; (2) mix of content and the process; and(3) the overlap between value creation and cap-ture. Value creation is divided into use value (asperceived by an individual) and exchange value(as the monetary compensation), and should berelated to the source and the target (individ-ual, organization, and society). Value creation ishighly subjective and context-specific but alwaysrooted in interactions. Value creation should beprimarily analyzed on the individual level, whilemost business model literature discuss value cre-ation on the organizational level. Value captureoverlaps value creation by discussing the sharingof value (value slippage) to society, organizations,and individuals [8].

Moore discusses value creation in a busi-ness ecosystem and the importance to havevalue-in-the-experience of customers, economicsof scale, and continuing innovation, while invest-ing in expanding communities of allies. He definesa business ecosystem as a complex structure ofinterested parties and communities interacting

with each other to produce and to consume goodsand services, in a partially intentional, highlyself-organizing, and even somewhat accidentalmanner [38]. In such a volatile and increasinglycomplex environment, successful companies can-not just add value, but instead need to addressthe value-creating system itself. They must rein-vent value, and work together with all stake-holders in the business ecosystem to co-producevalue [39].

The flexible nature of software-intensive prod-ucts opens up unique opportunities to quicklyreinvent and co-produce value, but also presentsnew challenges for SIPD companies in businessecosystems [37, 40]. Figure 1 illustrates an ex-ample of software-based value creation in anecosystem, highlighting three distinct, but over-lapping process areas: (1) core business processes,(2) product development, and (3) product inte-gration.

SIPD companies possess unique opportuni-ties to harvest the flexible nature of softwareand reinvent value by integrating and develop-ing native product support for each respectivearea and the business model(s). These areas areextensively discussed in the business model litera-ture, e.g., covering pure software business models[41], open source/mixed source [42] and digitaloptions [43], transitions from product-based busi-ness models to service-based models [44], or toindustrial product-service systems and use mod-els [37,45,46]. Even mechanical products rapidlybecome software-intensive products [47].

The software value map (SVM) [48] exploresthe different value perspectives and the chal-lenges of balancing the relevant value aspects insoftware development. The SVM is an extensivecollection of software value aspects categorizedin four perspectives3: customer value; the finan-cial perspective; internal business perspective;and the Innovation, market and intellectual per-spective on value. The SVM puts precise andexplicit terms on concepts discussed by Höflinger,

1Based on CEO Challenge 2004: Perspectives and Analysis, https://www.conference-board.org/publications/publicationdetail.cfm?publicationid=893, and revisted by http://www.floordaily.net/flooring-news/survey--most-ceos-say-flexibility-and-adapting-to.

2IBM’s global CEO report 2006: Business model innovation matters, http://www.emeraldinsight.com/doi/full/10.1108/10878570610701531.

3See http://www.softwarevaluemap.org for the SVM Tool and latest details, as it is continuously updated byinput from more than 50 companies world-wide, October 2016.

https://www.conference-board.org/publications/publicationdetail.cfm?publicationid=893

https://www.conference-board.org/publications/publicationdetail.cfm?publicationid=893

http://www.floordaily.net/flooring-news/survey--most-ceos-say-flexibility-and-adapting-to

http://www.floordaily.net/flooring-news/survey--most-ceos-say-flexibility-and-adapting-to

http://www.emeraldinsight.com/doi/full/10.1108/10878570610701531

http://www.emeraldinsight.com/doi/full/10.1108/10878570610701531

http://www.softwarevaluemap.org


Figure 1. Software-based value creation in a value delivery chain in a business ecosystem

e.g., know-how characteristics, value structure,financial value, social value, and organizationallearning. The SVM provides a necessary but of-ten neglected bridge between product strategy,value, and operationalization of software systemsand products in requirements elicitation, anddecision making.

In Figure 1, two companies, and a customerinteract in a business ecosystem. The softwareproducts are involved as agents via interfaces andfeatures along the value delivery chain. Value iscreated in the interaction between two stake-holders, indicated by the arrows between thestick-men and their smiley faces. A companyneeds to look beyond their borders to identify allstakeholders and possible interactions for valuecreation (at society, organizational, and individ-ual level).

Different aspects of value are created in theseinteractions, while external conditions and in-fluences shape the perception of value (as tech-nology and society advances), often resultingin a misalignment between expected and per-ceived value. BM (in a SIPD context) aims tosystematically capture, prioritize, and addresshow business logic, resources, and governanceshould be operationalized for optimal value cre-ation and value capture. A software product is

hence an essential part of the operationalizedbusiness model, both by acting as an agent tothe business model (the content, structure, andgovernance of transactions), as well as throughoptimizing a software product’s changeability[37] to adjust for external influences.

Figure 1 also illustrates the recursivenessand complexity of business models and soft-ware-based value creation. Each company typi-cally run their business model while the “overar-ching” business model for the business ecosystemcan be seen as an aggregation and collabora-tion of the “underlying” business models [28].Software Product C (e.g., a browser) is usingSoftware Product B (e.g., a crowd-funding ap-plication delivered as a cloud service), whichin turn is relying on Software Product A (e.g.,a database application delivered as a service).Each company develops their software product(s)based on their (business model’s) vision andgoals. They constantly need adjusting for exter-nal influences, using requirement engineering toconstrain the vision and goals into an “optimal”realization (time, opportunities, risks, features,and resources) of the software product. A soft-ware product should have features addressing(all) the needs of (all) stakeholders (throughoutthe complete value delivery chain). It must also


support any stakeholders’ interaction with thesoftware product throughout the product’s en-tire life-cycle (from the idea, design, production,commissioning, usage, to de-commissioning andobsolescence). Such role-based interaction is il-lustrated in the figure with features, interfaces,bi-directional arrows and the stick-men. An in-teraction can also be a non-human interactionbetween two software products, entirely inter-nal to a company, or any combination thereof.These interactions occur at all levels in activi-ties between actors, within and across companyborders, as well as within different life-cyclesof the value delivery chain. In a business model,a transaction is an aggregation of such role-basedinteractions where the exchange of information,goods, payments, and feedback are not neces-sarily synchronized. Also, the different softwareproducts’ life-cycles interact and overlap. Thisputs new requirements on the software productto more efficiently handle the introduction of newinteractions and collaborations, e.g., customersbeing part of the design or test of Company B’ssoftware product while Company A and B entera partnership agreement to share costs and rev-enue [28]. For SIPD, this creates a tight, highlyrecursive relationship between BM and the soft-ware products.

3. Related work

Several prominent literature reviews are pub-lished on the topics of business models. Forbrevity, we focus on recent publications highlight-ing aspects relevant for performance [7,11,12,49].Common to all reviews is the lack of empiricalevidence that using BM to evolve the businessmodel increases a company’s effectiveness andefficiency. Lambert and Davidson summarize 40publications and report that choosing the rightbusiness model is one factor for a company’s suc-cess based on evidence of a relationship betweensuccess, business models, and business modelinnovation. They conclude that the studies mea-sure and report what is the current situation, butno empirical research aims to predict companysuccess.

Three of the reviews [7,11,12] highlight thetwo major challenges in current research on busi-ness models: 1) that business model researchis too dispersed and needs a consolidation ofconcepts; and 2) that it is difficult to connectstrategy (via business model) to execution, whilecapturing and handling the needed dynamics oftoday’s global and multi-stakeholder businessenvironments. Other prominent researchers alsohighlight the lack of a consolidated body of knowl-edge and concepts [9,23,50,51], indicating a gapin understanding BM’s real-world effects.

Business models for explaining a company’sperformance are frequently discussed both con-ceptually [52, 53] as well as empirically [54–56].Hacklin and Wallnöfer conclude that the businessmodel acts more as a symbolic artifact and notas an analytic tool. Zott and Amit report em-pirical evidence suggesting that business modeldesign can provide a competitive advantage, butdoes not provide conclusions that employingBM to evolve the business model will improvea company’s effectiveness and efficiency. Lambertand Davidson studied the relationship betweencompany success, business models and businessmodel innovation. These studies all measure andreport what is the current situation, but thereis no empirical research that aims to predictcompany success or to conclude that businessmodeling enables effectiveness and efficiency ofa company [49].

Osterwalder et al. advocate formalization ofbusiness models using IS/IT tools and an exper-imental approach “when-and-how-to-build” [57].Their eight propositions to be observed and even-tually tested seems still be equally valid: 1) userigorous meta-models; 2) increase understandingbusiness and IS/IT; 3) improve integration busi-ness and IS/IT; 4) facilitate and improve IS/ITchoices infrastructure/applications; 5) facilitatechoices IS role and structure; 6) help definingcompany’s goals; 7) facilitate identification ofkey indicators; 8) externalize, map and storeknowledge of value creation logic [9].

Giessmann et al. extend Osterwalder et al.’spropositions to build a model that can analyzeand compare business models, but their workdoes not address the issues of aligning and daily


execution of a business model [58]. Salgado et al.also build on Osterwalder’s business model can-vas (BMC) and discuss how to generate a BMCfrom business goals, rules, and processes, but donot further connect the results to the IS/IT real-ization and daily operations [59]. They also dis-cuss the alignment between business and IS/IT(from the lens of business model artifacts, enter-prise modeling, and strategy and goal modeling)and formulate the main challenge as Achievingalignment per se is not enough, organizationshave to reach the alignment state and maintainit alongside its evolution [34].

The literature indicates a research gap be-tween modeling the business and executing thebusiness model and more specifically, do busi-ness modeling increase a company’s effectivenessand efficiency? Höflinger’s framework extensivelybuilds on the literature but does not empiricallydefine or explore his angle of superior perfor-mance, nor the dynamics of a business modelrelated to value. Further, he does not explore howthe learning of an organization interacts with thedesign of, the representation of, and experimen-tation with a business model [7]. Rohrbeck et al.stop at the preparation for development and donot provide further insights into the mechanicsneeded for actual experimentation and validationof a business model [28]. Richter et al. discussflexibility and value as a way to deal with changeand implementation of business models. Theyconclude that further work is needed to betterunderstand inter-firm governance structure [37].Ballon proposes an analytical framework for mak-ing the scope for choice explicit and concludesthat further work is needed to make interde-pendencies of parameters explicit and to extendthe model in a more prospective and predictivesense [33].

4. Methodology

4.1. Research questions

We used software and software-intensive productsas the unit of analysis. The rationale comes fromthe central role that software-intensive productplay in the on-going business environment digital-

ization transformation. We focus on the followingtwo research questions:RQ1: What benefits and challenges of businessmodeling are reported in the literature?RQ2: What effects related to effectiveness andefficiency of business modeling are reported inthe literature?

We used RQ1 to investigate the contextualsetting for business modeling and to compareand analyze the reported effects on efficiency andeffectiveness. The on-going business environmentdigitalization transformation heavily depends onflexible and scalable software solutions. Thereforewe limit the scope to business modeling for SIPDcompanies developing software-intense productsand services. The research process executed inthis study is outlined in Figure 2.

4.2. The snowball methodology

Our systematic literature review (SLR) method-ology is based on the guidelines for snowballingliterature search proposed by Wohlin [60]. Thesnowballing methodology is considered less noisycompared to a similar database-search basedmethodology and the critical step for a successfulsnowballing is to choose a good tentative startset characterized by: 1) studies from differentcommunities; 2) size appropriate for the studiedarea; 3) diversity of publishers, years, and au-thors; and 4) is based on the research questionsand keyword. The complete study was conductedin four steps, outlined in the subsections belowand depicted in Figure 2. We screened 16 320papers resulting in 57 papers included in thestudy.

4.2.1. Step 1: Design of the literature review

To minimize the author-bias and to prepare fora cross-disciplinary study (business managementand software engineering), we performed twoopen-ended interviews to identify further readingto understand the terminology to formulate ourresearch questions. These interviews helped usto decide upon the methodology, validity risks,inclusion criteria (IC) and data extraction prop-erties. We also created a study protocol and doc-umented each step and decision. The same IC


Table 1. Search strings for start set

Id Terms

SS1 (“business model” OR “business ecosystem”) AND “value creation” AND “strategy”SS2 (“business modelling” OR “business modeling” OR “business ecosystem”) AND “business strat-

egy” AND “value creation” AND (”effectiveness” OR “efficiency” OR “business flexibility” OR“modularity” OR ”variability in realization” OR ”governance” OR “multi-business”)

were used defining both the start set and in thefollowing snowball iterations, see Appendix B.

4.2.2. Step 2: Defining the start set

We used a database search in Google Scholarto find the start set and recommendations fromthe interviewed experts. The two initial inter-views (60-minutes, open-ended interview withthe question Does business modeling enable im-provements in effectiveness and efficiency fora company?) with experts in software engineer-ing (telecommunication industry with 25 years ofexperience) and business management (professorin production management) resulted in a startingpoint of:– four recommended studies, of which Höflinger

also ended up in the start set [7];– a wide multi-disciplinary map of subject ar-

eas: computer science; software engineering;business management and accounting; eco-nomics, econometrics and finance; organiza-tion management; and decision science;

– additional keywords – open innovation, strate-gic management, value creation, value cap-ture, flexibility, business model innovation,business ecosystem, organizational theory,knowledge management, service science, en-terprise architecture, software product lines,open source, and product service systems.After further search in Google Scholar for

definitions on these keywords, we created a rec-ommended Golden Set (31 papers) from whichwe derived a collection of definitions to helpus penetrate the terminology. The snowballingmethodology recommends using Google Scholarto avoid any bias on specific publishers [60]. Thedefinitions helped us develop the search strings(SS). We used a traditional search schema with

iterative clustering to reduce the number of hitswhile minimizing noise (initially in Scopus sinceit contains all the subject areas). We ended upwith two search strings4, see Table 1, used toquery six databases, see Figure 2.

Executing SS1 and SS2 (limited to title-ab-stract-keywords) resulted in 2948 papers, seeFigure 2. The first author applied the inclusion cri-teria on titles and abstracts, and 2378 papers wereremoved. The remaining 570 papers were put in anexcel sheet so duplicates and not peer-reviewed pa-pers could be discarded. The final 477 papers werescreened more thoroughly (abstract, introduc-tion, conclusion) for IC and the result discussedand validated with the second author, leavingnine papers to be included in the start set. Onepaper recommended by the experts in businessmanagement was also included in the start set.

4.2.3. Step 3: Execute snowballing iterations

The first author collected the references of ci-tations to the papers selected in each iteration.Next, we applied inclusion criteria and calcu-lated the Cohen’s Kappa in all iterations, seesection 4.3.

In total, we screened 10 414 citations and 2958references, see Figure 2. Iteration 1 covered thestart set and resulted in 35 selected studies (outof 612 references and 249 citations). Iteration 2resulted in 2011 references and 10 134 citations.The noise in citations is one of the downsidesreported for the snowballing methodology, andwe applied an initial pre-screening (language, ti-tle, abbreviated abstract) giving us a remaining1335 citations to screen. By having the candidatelist in Excel, it was easy to detect all duplicates.We selected 11 studies in iteration 2. Iteration 3rendered 313 references and 30 citations resulting

4SS1 uses stemming and SS2 doesn’t. Also, “multi-business” was added upon recommendation of industry expert,since executing several business models in parallel is a significant challenge for large SIPD companies.


Figure 2. Research methodology overview

in one new paper selected. We got a natural stopof the snowballing procedure by iteration 4 withno more studies discovered resulting in a total of10+35+11+1 = 57 studies selected for analysis,see Appendix A for a complete list.

4.2.4. Step 4: Data extraction, analysis,and synthesis

Appendix C outlines the data extraction prop-erties (EP) used in this study. ATLAS Ti5 andExcel were used to keep track of and analyze re-sults as well as synthesize extracted information.The extraction was done by the first author andvalidated by the other authors, see section 4.3.

Properties EP1–EP4 were evaluated per pa-per and used to analyze the relevance to industryfor each paper’s contribution. The property EP3(Rigor & Relevance) was also used for qualityassessment, see extracted raw data per paperin Appendix A and detailed calculations in Ap-pendix C. It helped us to evaluate generalizablity

of the results, see section 4.3. Open coding [61]was used for properties EP5–EP9 and the ex-tracted data was thematically analyzed. Prop-erties EP5–EP9 helped us synthesize results re-garding BM as phenomena as well as to identifypotential research gaps.

The results were iterated in two phases (a)RQ1 and (b) RQ2. For each phase, the first au-thor prepared a summary of listed quotationsfrom all studies. The list was then reviewedagainst the extracted result, and the first au-thor had to explain a summary of each paper’sfindings to the reviewer. Phase (a) were reviewedby the second and third author, while phase (b)were reviewed by the second author.

4.3. Validity threats

We adopted the validity guidelines suggested byRuneson et al. [62]. An extensive industrial ex-perience of the authors may have influenced theaims of the study with a stronger bias towards

5Software for Qualitative Data Analysis, http://atlasti.com/.

http://atlasti.com/


solutions. We mitigated that bias by two initialinterviews and an iterative refinement of the re-search questions and also by applying a groundedtheory approach [61], fostering a focus on themerits of each paper before an end-to-end per-spective could be evaluated.

The selected ten papers in the start set arehighly heterogeneous and therefore minimize thebias on specific author or terminology. Similarly,we mitigated the author’s bias by calculatingthe Kappa coefficient when selecting the startset papers. The Kappa analysis was done bythe first and second authors, and the value wasκ = 0.566 and later increased to κ = 0.638. TheKappa analysis was also performed during thefirst snowballing iteration on 12% of the studieswith a resulting value of κ = 0.763. These valuesrepresent sufficient agreement and increase thevalidity of the study.

To mitigate author bias during extraction, sixrandom studies were selected (of the 57 studies)and extracted by the first and second authors.The validation showed a discrepancy of one paperfor extraction properties EP1–EP4 and after fur-ther discussion full agreement was reached. Also,the results to the RQs (EP5–EP9) was iteratedin two phases, and each phase was presented byfirst author before discussed and evaluated by atleast one more researcher.

Rigor and relevance analysis was applied tomitigate potential threats to conclusion valid-ity. The rigor classification based on softwareengineering literature was also adapted for busi-ness modeling literature. The relevance param-eter was coded using binary weights (0, 1, 2,and 4 instead of the recommended 0 and 1).We also decided to add property EP4 to specif-ically address the relevance of a paper’s contentconcerning our RQs (since the property EP3and its’ relevance aspects only consider the re-search method and context of a paper). Thisprovided higher resolution when discussing therelevance and when thematically comparing thepapers. The extraction of results was iterativelyreviewed and discussed with second and thirdauthors. We minimized potential internal valid-ity threats by following the systematic mappingstudy guidelines, creating a review protocol and

sharing the work associated with data extractionand analysis.

Since this study covers studies from a wideset of research fields, the semantics (and context)of words can often be misleading. We addressedthis by our choice of a snowballing methodologyin combination with a rigor design to identifythe start set. Moreover, we used open coding(inspired by grounded theory [61]) to synthesizeand harmonize language between the differentresearch fields.

Because of the interdisciplinary nature of thisstudy, the risk remains that some aspects areunderrepresented and other aspects are overrep-resented. In particular business model innovationor business process modeling seems to be heavilyresearched in the business management and thecomputer science community. However, we de-cided to limit the scope in these dimensions sinceour primary interest is the interplay betweenthe strategic intentions, the design of a businessmodel, the realization of it, and the resulting ef-fects on efficiency and effectiveness, rather thandetails on how individual steps are performed.

We selected our start set studies from dif-ferent research disciplines and these studies areconducted using many different research meth-ods which improve the external validity of ourliterature review. Even though the start set iscarefully chosen and includes publication years(2004–2014) there are only 17 (out of 57) paperspublished during 2013–2015.

5. Results and analysis

Table 2 shows results related to research ques-tions mapped to each paper’s context (data ex-traction property EP4, see Appendix refapp:C),including frequency and summarizing comments.Using inclusion criteria IC2 and IC3 we inves-tigated if the papers address flexibility withoutfurther exploring the efficiency or effectiveness.

74% of the identified studies (EP4, categories2 and 3) focus on the business model constructrather than the BM as a practice. One reason forthis could be that BM as a practice is a broad, di-verse topic forcing researchers to limit the scope


Table 2. Results mapped to research questions and paper context

RQs/ICs

Businessmodeling(1)

Businessmodel (2)

Other (3) Sumof pa-pers

Comment

RQ1 2, 6, 15, 17,18, 35, 36,37, 41, 49,51, 52, 53,54, 56

1, 3, 5, 7,9, 13, 14, 16,19, 20, 21,22, 24, 29,32, 33, 39,40, 45

8, 10, 12, 26,30, 31, 34,38, 42, 43,46, 48, 55,57, 58, 59

50 Scattered in a multitude of practices andframeworks. Results suggest lack a system-atic alignment of contextual informationhindering re-use and integration of prac-tices

RQ2 17, 35, 37,54, 56

1, 5, 24, 29,32, 45

8, 42 13 Quotes on effectiveness and efficiency arenot differentiated nor substantiated

IC2 2, 6, 17, 18,35, 36, 37,41, 49, 52,53, 54

1, 3, 5, 7,9, 13, 14, 19,20, 22, 24,27, 29, 33,39, 40, 45

8, 10, 12, 26,30, 31, 34,38, 48, 55,57, 58, 59

42 Many papers reflect over flexibility. Gover-nance is important for understanding thevalue (and cost) of (the right) flexibility inorder to optimize the value creation andvalue capture

IC3 2, 6, 15, 18,35, 37, 49,51, 52, 54, 56

1, 3, 5, 7,9, 13, 16, 19,21, 22, 24,27, 29, 32,33, 45

10, 12, 26,31, 34, 43,46, 55

35 Variability in the realization is an impor-tant aspect of flexibility and should bea part of the business modeling analysis

Sumof pa-pers

15 (29%) 20 (39%) 16 (31%) The % is calculated of the 51 papers adress-ing RQs+ICs. 6 papers of the total 57 se-lected papers did not specifically addressany of the RQs+ICs. They all belonged tocategory 3: Other

Hitrate

33% (5) 30% (6) 9% (2) The ‘hit rate’ is the ratio of papers address-ing both RQs. For category 3 the ratio in-clude the 6 papers (not listed in the Table)not addressing any RQs

by addressing some aspects of a business modelconstruct rather than BM as an activity or pro-cess. Still, only 33% of the paper address bothRQ1 and RQ2.

The number of papers addressing multipleRQ+IC is growing since 2005. As the area be-comes more mature, it is also becoming morecomplex, multifaceted, and cross-disciplinary.This trend is also indicated by Kindström wherehe states that companies need to focus on allareas of their business models in a holistic fash-ion, and not just change isolated elements [P24].Similar, Reim et al. concludes that more researchefforts are needed on the complicated relation-ship between strategic and operational levels [P3].This could be one of the reasons why businessmodel research is still scattered and disperse. Toevaluate BM efficiency, it is therefore essentialto connect the business strategy via the business

model to the execution of the business modelwith traceability to daily operations and results.

We used Rigor and Relevance (EP3) to an-alyze the identified papers, see Figure 3 andAppendix A. 60% of the studies received in-dustry relevance scores greater than 7, repre-senting a good balance between state-of-art andstate-of-practice. A majority of these studies (20)score 15 (highest), and additional eight studiesscore > 9 (two or more conditions met). Theincluded literature reviews [P3, P9, P29, P40]have (as expected) a relevance score = 0 withacceptable rigor scores (>= 1). The remaining 19studies with a non-industry relevance score, dis-cuss specific topics or more general frameworksand methods/aspects (related to BM) dividedon: strategy [P15, P19]; life cycles [P25, P28]; ef-fectiveness and efficiency [P35]; flexibility [P27];static/dynamic [P14, P34]; or frameworks, meth-


Figure 3. Papers plotted for frequency (size), rigor (X-axis) and relevance (Y-axis) scores,and paper context (font)

ods and models [P8, P10, P16, P18, P22, P31,P32, P41, P44, P57, P59].

45% of the studies are coded with a low rigor(score 0 and 0.5) where 11% only describe thecontext, but not mentioning any design or valid-ity aspects. The validity aspect is the single mostlacking aspect lowering the rigor in 54% of the22 studies with medium rigor (score 1, 1.5 and 2).Different research fields are different regardingmaturity, methodology, and best practices onhow to report the research, which we believe arethe main reasons affecting the rigor aspect.

5.1. Benefits and challenges associatedwith business modeling (RQ1)

We extracted 263 quotes of purpose, benefitsand challenges of business modeling (EP5), seeAppendix D. Quotes of purpose (P) often sets thegeneral context, while quotes of challenges (C)or benefits (B) often are reflections of how wella solution to a specific problem works. Benefitsrefer to a solution with good enough result while

challenges refer to potential issues to obtain a sat-isfactory result (judged by specific qualities andcontextual factors). We identified the followingcommon areas (rows in Appendix D): 1) value cre-ation/capture; 2) cost/revenue; 3) mind-set andknowledge; 4) means6 (mission, strategy, tactics,directives, organization, and resources); 5) ends6(vision, goals, and objectives); and 6) assessment6(decision control, clarity, visualization, influencer,etc.).

Our literature review results suggest that theoverarching purpose found for BM is for a com-pany to stay competitive and improve its businessresults. The quotes of purpose are often overlap-ping and cover a wide variety of more specifictopics, like managing individual business aspects(e.g., offerings, market, cost and revenue), captur-ing the business logic and activity systems, overto a holistic nature like “operationalize strategy”,appropriate value from technology, or managingvalue (co-creation, capture, creation) and part-ners. Investigating the quotes further, we identi-fied three primary contexts for BM (columns in

6We use the terms assessment, ends, and means as defined in 2015 by Business Motivation Model SpecificationVersion 1.3. http://www.omg.org/spec/BMM/. Accessed 2 Nov 2017.

http://www.omg.org/spec/BMM/


Figure 4. Quotes binned on purpose, benefits+challenges, and distributed over the primary contexts

Appendix D): 1) Strategy and planning; 2) Dailyoperations (executing strategies and plans); and3) Governance and communication.

To analyze potential ambiguity (per paper)between the primary context of purpose quotesvs. the primary context of benefits/challengesquotes, each quote is tagged with Paper ID, Typeof quote (one of P, B, C), and primary context(one of 1, 2, 3). Figure 4 illustrates the number ofpapers adhering to different contextual coherencebins distributed over the three primary contexts.We define the five contextual coherence bins. Bin0 equals a paper having zero quotes in a primarycontext. Bin 1 equals a paper having quotes of Pand B/C only in different primary context. Bin2 equals a paper having only quotes (B/C) fora primary context. Bin 3 equals a paper havingonly quotes (P) for a primary context, and Bin4 equals a paper having quotes of both P andB/C in same primary context.

Strongest contextual coherence is found in bin4, with the highest ratio for the primary context“Governance & communication” at 16% (15 pa-pers). The most significant contextual ambiguity(bin 1) is found in 4 papers [P8, P13, P19, P49]where a purpose is stated in one primary contextwhile the benefit or challenge is claimed in an-other primary context without specific detailingthe relationship. Romero & Molina discuss thepurpose of value co-creation, as a complicatedcooperative process (speed, coordination, com-

promise) with the challenge of managing theexperience-sharing network, and how that af-fects the business modeling [P8]. Chesbrough dis-cusses business model innovation with purposesrelated to formulating competitive advantage,value proposition and value chain definition whileconcluding challenges as a lack of tool supportand continuous learning associated with BM ex-perimentation [P13]. Richardsson discusses thepurpose of formulating and achieving goals andobjectives while concluding challenges as manag-ing the different abstraction levels towards exe-cution and getting the details right [P19]. Eurichet al. discuss the purpose of transforming thebusiness opportunity into an organizational im-plementation via experimentation and businessmodel fit, while concluding challenges in practicalaspects like lack of details, not aligned design pro-cesses, disregard of external influences, etc. [P49].Moreover, a significant portion of the paperslack statements on purpose, benefit, or challengemaking a discussion around effectiveness and effi-ciency more challenging due to vague contextualinformation. Our results highlight a challengingissue how to effectively and efficiently definingcontexts to improve understanding and commu-nication in BM literature.

The importance of contextual information ismentioned by seven studies [P8, P17, P18, P20,P25, P51, P59], but no author goes as far as tosuggest how to describe or represent the contex-


tual information. At the same time, the currentresearch on context description in software en-gineering provides a useful checklist on contextfacets (product, processes, people, practices andtechniques, and organization and market) [21].However, these context facets are ambiguous inthemselves, e.g., a market consist of products,customers, and organizations, a product couldbe a service and therefore include a process, etc.As a reflection of the identified challenges andclaimed benefits, related to the paper’s contribu-tion to practices and methods for BM (includ-ing effects on effectiveness and efficiency), theunderlying purpose is contextually vague withstatements like “operationalize strategy” [P36,P37], or “deal with uncertainty” [P2, P52, P54].The papers offer no empirical evidence to supportthat the purpose can be realized with claimedbenefit nor do they quantify the extent of thechallenges.

Similarities between the quotes on benefitsand challenges are found, but only eight quotesare reported by multiple authors, for example:“(−) difficult managing dynamics (agility, adapt-ability, planning, decision) for alignment to envi-ronment and other organizations” [P2, P5, P7,P9, P36]; “(−) hard to visualize, document andshare” [P26, P32]; “(−) difficult to mobilize andalign available resource in time” [P9, P15]; “(+)better understanding, better language and legit-imacy” [P17, P32]. We speculate that this lowlevel of coherence between the papers is a resultof the wide topical area of BM. We also note thatseven of these eight quotes discuss common top-ics of governance (“handle dynamics”, “align”)and knowledge (“understanding”, “sharing”, “le-gitimacy”, etc.), while the remaining statementcovers value creation.

There are also cases where the same type ofstatement is argued both as benefit and chal-lenge (by different authors). For example, (+)“building better strategies” [P32] vs. (−) “BMdesign requires better integration with strategyanalysis” [P37] or (+) “improves dealing withuncertainty” [P2] vs. (−) “difficult to deal withuncertainty, complexity and dynamism” [P54]or (+) “improves alignment of strategy, organi-zation and technology and integration business

IS/IT domains” [P32] vs. (−) “hard to reachand maintain alignment of business model andinformation system model” [P59]. This kind ofambiguity can be a result of the wide topical areaof BM in combination with a poorly specifiedcontextual setting, opening up for a differentinterpretation of results.

The majority of the quotes are found in theunion of (Governance) | (Mindset, Knowledge)| (Assessment) indicating that learning (knowl-edge) and control (governance) is key to BM.This is also backed by [P5, P13, P32, P51] whichdiscuss the importance of experimentation andlearning to adapt to the changing environment.The changing environment is also highlighted by[P2, P9, P49] as a challenging fact of businessmodels, and as McGrath concludes, everythingcannot be planned, but rather adapted to a suit-able fit [P18]. In the same vein, we notice thevast number of papers belonging to bin 0, 2, and3, indicating that a majority of the papers foucson a single primary context of BM, rather thanconnecting the strategy to the execution and eval-uating the business outcome (as a consequenceof the BM practice).

Summarizing the results, the most commonchallenge is how to deal with the dynamics of busi-ness models [P2, P5, P7, P9, P36] and most of thequotes on challenges relate to the non-existing so-lutions for governance (representation, simulation,decision-support, and feedback) of the proposedframeworks and methods. Since governance isnot addressed, each BM method or frameworkmay work in its’ specific context, but taken outof context or combined with other methods mayfail to deliver the claimed benefits. Also, thequotes of benefits are unsubstantiated or claimedwith limited empirical evidence (except for anempirical case which evaluates and comparesuser’s understanding of two value models [P35]).

5.2. What impact does BM have oneffectiveness and efficiency (RQ2)?

Only two studies make a clear distinction be-tween the terms effectiveness and efficiency [P5,P35] where Chew and Buder & Felden bothspecifically link effectiveness to quality and ef-


ficiency to effort to perform a task. Zott et al.recognize efficiency as an important value driver,and that any value driver can enhance the effec-tiveness of the other drivers [P29]. Osterwalderet al. connect efficiency to infrastructure manage-ment while effectiveness is indirectly connectedto value [P32]. Chew and Romero & Molina con-nect effectiveness to customer experience [P5, P8].Mason & Mouzas argue efficiency is a product ofcareful management of resources and capabilitiesdriven by a “network focused” approach whileeffectiveness (via marketing) is a product of beingmarket-focused to keep in touch with changingcustomer needs by flexible products and serviceofferings [P58]. The terms are also used on differ-ent abstraction levels hindering in-depth analysis.We believe this is a likely result due to the combi-nation of: 1) none of the 57 studies have researchquestions that directly address effectiveness andefficiency; 2) that business model research is stillnot coherent with a consolidated view of whata business model is used and useful for; and 3)few scholars address both primary contexts ofstrategy and the execution making an evaluationof effectiveness and efficiency difficult.

Measurements of effectiveness, efficiency, andcompany’s performance (as an expected outcomeof efficiency and effectiveness improvements) areneither sufficiently described nor substantiated.Measurements of effectiveness were only explic-itly defined by Buder & Felden where they useda ratio of correctly answered questions to evalu-ate the effectiveness of individual methods aboutunderstanding value [P35]. No explicit measure-ments on efficiency or company’s performancewere found amongst the papers, except for An-dries & Debackere who suggested company’s sur-vival rate to measure its performance for newtechnology-based business models [P42]. Ghezzidiscussed how discontinuity can be detected be-fore it affects a company’s performance but doesnot mention how to measure the performance[P37]. A company’s performance is also referredto by different terms but not further substanti-ated, for example by profitability [P29], valuecreation [P29], organizational performance [P29],operating cost or gains in productivity [P54]. Wefound no empirical evidence (except [P42]) to

substantiate claims on effectiveness and efficiency.We also note that all 13 papers addressing RQ2also address aspects of flexibility and variabilityin the realization (IC2 and IC3, see Table 2).

Indirect effects on effectiveness (and efficiencyvia profitability) are reported by three papers[P24, P29, P37]. Kindström discusses the tran-sition to the service-based business model asa key to remaining competitive [P24]. He does notmake any specific claims about effectiveness orefficiency, but proposes focusing research effortson: 1) how to industrialize service offerings toa larger scale; and 2) understanding how a tran-sition to service-based business models affectsprofitability and growth. Zott et al. in their litera-ture review acknowledge the possible contingenteffect of BM linking product market strategyand company performance [P29]. They also referto a study by at IBM Global Business Servicesin 2006 that says financial out-performers puttwice the effort on business model innovationcompared to under-performers, but do not fur-ther elaborate as on how. Ghezzi looks at thestrategic planning process and BM under dis-continuity [P37]. He concludes that the ‘busi-ness model parameters mix’, as derived fromthe different business model blocks, directly af-fects the company’s performance. He providesa strategy-analysis tool based on BM, VN, andRM constructs (business model, value network,resource management), to detect what is chang-ing in the company’s strategy when discontin-uation occurs, but he does not discuss in anydetail how to derive any changes in effectivenessor efficiency.

Summarizing the results, we found limitedempirical results indicating that BM has an over-all effect on a company’s results regarding ef-fectiveness and efficiency improvements. It isalso not possible to judge whether a favorableoutcome can be achieved in a scenario of contin-uous (experimental) BM, or it is just a result ofa one-time activity to modify the business model.Also, we note that all 13 papers addressing RQ2also address aspects of flexibility and variabilityin the realization. These limited results promptus to do a contextual analysis of the effectivenessand efficiency of BM.


5.3. Contextual analysis of effectivenessand efficiency

We base our analysis on the two main contextualBM settings: 1) the business model realizationshould increase a company’s effectiveness andefficiency; and 2) the effectiveness and efficiencyof the BM process itself.

For increasing effectiveness and effi-ciency (contextual BM setting 1), we foundthe same three primary contexts as reportedin Section 5.1: 1) strategy and planning; 2) dailyoperations (executing strategies and plans); and3) governance and communication, see Table 3.From these contexts, we identified three patterns(full, partial, and single) describing whether a pa-per covers all three contexts or parts of them.The patterns are derived from the first threecolumns (define, execute, and governance) inTable 3. Full means that the paper does addresstopics in planning and strategy, daily execution,plus governance and communication contexts.Partial refers to any combination of two con-texts, while single refers to only one context.We also analyzed the papers according to thethree key areas aggregated from the studies: valuecreation/capture; decision support; mindset andknowledge.

The BM process’ effectiveness and effi-ciency (contextual BM setting 2) are discussedby 3 of the 13 studies [P35, P54, P56]. Buder &Felden recognize the hurdle of keeping modelsconsistent during transformations and suggesta specific value representation model as a rem-edy [P35]. Salgado et al. propose a method formodeling and visualizing requirements on the de-fine and execute processes of the business model[P56]. Both studies offer limited empirical evalua-tions. Meier & Bosslau recognize the importanceof a continuous, integrated BM to capture thedynamics of the ecosystem [P54]. It is the onlypaper clearly discussing the importance of notseparating the process of BM from the actual de-fine and execute processes of the business model.However, they do not quantify any effects on ef-fectiveness and efficiency, while concluding thattools are a necessary focus for further research.We believe the lack of empirical results is a direct

consequence of: 1) the wide contextual settingsfor business model research; and 2) the lack ofconsolidated view on what a business model isused and useful for. Given our study’s primaryfocus (contextual setting 1), we also interpret theratio of papers addressing our main contextualsetting (77%) as a quality measure of our studydesign.

Full pattern category papers [P1, P5, P8,P24, P29, P54] advocate that to yield effective-ness and efficiency, the overall focus is how theplan/strategy/goal should be aligned with theexecution of the strategy. Woodard et al. dis-cuss how “design moves” enable rapid productdevelopment in a new domain with fierce compe-tition and how to formulate and execute digitalbusiness strategies (align strategy to execution)based on option value and technical depth [P1].They propose decision-support via option valueand technical depth to integrate the perspec-tives of designers and corporate strategies. Theyempirically illustrate effectiveness and efficiencyfrom a set of design moves but do not state onwhat level anything became more efficient.

A transition into service-based business mod-els to improve competitiveness and efficiency ofthe business model is proposed by three papers[P5, P54, P24]. Chew argues that business modeldesign impacts directly financial performance butdoes not state how nor to what extent it affectseffectiveness [P5]. Effectiveness is a result of ser-vice variability and aligning the three contiguousprocesses for optimal value co-creation (customervalue-creating, supplier value-creating, and theservice encounter processes). He focuses on thedefine process with a service design concept tounderstand the customer needs and value ap-propriation, and concludes that execution alsorequires support by a corresponding modular orga-nizational architecture as well as IS architecture.Meier & Bosslau discuss the difficulties whentransitioning from a product-centric businessmodel into a product-service centric model, withempirical findings that only 21% of manufactur-ing companies succeed in this transition [P54].The fundamental problems are: a drop in effi-ciency, diversified portfolio, and an increasedcost due to an increased product-service port-


Table 3. Identified effects on effectiveness and efficiency

Pattern andkey areas

Strategy & planning(Define)

Daily operations(Execute)

Governance &communication

Business modeling

(contextual setting 1) (contextual setting 1) (contextual setting 1) (contextual setting 2)

Full patternP1, P5, P8, P24,P29, P54

x x x P54

Partial patternP32, P37, P56 x – x P56P42 x x – –

Single patternP17, P35, P45 x – – P35

Value creation/Value capture

Concept of designmoves [P1]Service conceptdesign, service design,customer experiencedesign, servicearchitecture design[P5]Effective productmarket strategy [P29]Business processmodeling efficiency[P35]Cumulative changeshave a positive effecton success rate inimmature markets[P42]

Concept of designcapital [P1]Adaptations to initialBM are crucial, over-andunder-adaptationseffect performance[P42]The availability ofresources andcapabilities are moreimportant to qualityof adaptation [P42]

Transition toservice-basedbusiness modelimproves profitability[P24]Dynamic businessmodels (withflexibility) areimportant fora successful transitionto service-basedbusiness models [P54]

Modeling overhead intransformation andreduction to maintainconsistency [P35]

Decisionsupport

Provide relevantinformation for nextstage [P17]Strategic tools,business model, valuenetwork, resourcemanagement, signalradical change [P37]Empirical findings oninstrumentalefficiency for businessmodeling show noconvergent results[P45]Process, goals, rulesimproves traceability[P56]

Decision-support viaoption value andtechnical depth [P1]Representation ofinformation toenhance pragmaticvalidity [P17]Foundation forimproved speed toreact on externalevent and businessenvironment [P32]

Quantitativemodeling andsimulation is vital incontinuous loops[P54]Process, goals, rulesimproves traceability[P56]

–

Mindset andknowledge

– Capitalize user’sknowledge forinnovation (ideageneration,prototyping) [P8]Cumulative changeshave a positive effecton learning andsuccess rate [P42]

Formalizing activitiesforces implicitunderstandingsbecome explicit [P17]Generating andtransferring ofinsights is key forreuse, e.g., businessmodel cockpit [P54]

Generating andtransferring ofinsights is essentialfor reuse [P54]


folio without a matching increase in revenue.They propose an iterative learning process basedon an integrated business model design and en-gineering using System Dynamics (SD). SD isused to specify the business models run-timebehavior over time, but they conclude that theprovision and further development of this ap-proach are crucial in further studies. Kindströmidentifies vital aspects in define, execute andgovernance when changing into a service-basedbusiness model, and also recognizes the challengeof staying profitable [P24]. However, he makes nospecific contribution how to improve efficiency oreffectiveness and concludes that more researchis needed to link a transition to profitability andgrowth.

To enhance the effectiveness of collabo-rative networked organizations, Romero &Molina propose an experience-centric networkreference framework based on open-businessmodels (co-innovation/open innovation) [P8].By integrating a multi-value perspective witha multi-stakeholder approach, one can capitalizeon the networked organization’s knowledge toachieve better business models (e.g., better riskmanagement and transparency through valueco-creation). They present no evidence for im-proved effectiveness or efficiency.

Partial pattern category papers [P32, P37,P42, P56] focus on the define process in combi-nation with governance to ensure the expectedresults. Osterwalder et al. discuss how a formal-ized model can help to react to external eventswith speed and effectiveness, but presents noempirical evidence thereof [P32]. Salgado et al.argue that the gap in the business-IS/IT dialogue,which in turn leads to inefficient and non-effectiveIS/IT solutions, partly comes from: 1) the lackof formality; and 2) high dependency on spe-cific and skilled analysts, when deriving IS/ITrequirements from business goals [P56]. Theypropose the use of PGR (process-level use cases,goals, and rules) to improve traceability and thealignment of Business and IS/IT as a way toimprove effectiveness (of both developing andrunning the IS/IT solution). To close the gap inthe business-IS/IT dialog and increase efficiency,they propose a method how to generate a BMC

from goals and rules to improve decision mak-ing and increase traceability. The method hasonly been tested on a small, manual scale withconsiderable limitations: 1) a high dependencyon individual analysts and their knowledge andbusiness heuristics; and 2) limited scope due tothe amount of human resources needed. Conclu-sions on effectiveness and efficiency for their workare too early to derive. Ghezzi discusses businessstrategy under discontinuity and presents threetools to help managers identify a signaling “vec-tor of inputs” to trigger a strategic re-planningprocess [P37]. He refers to the relation betweenthe business model performance and a company’sperformance but makes no claims on effectivenessor efficiency with his contribution. Andries & De-backere instead look at the define and executeprocesses in their discussion how adaptation andperformance are related to new technology-basedbusinesses [P42]. They conclude that businessmodel adaptation is beneficial in less mature,capital-intensive and high-velocity businesses, asit reduces failure rates in dependent businessunits. However, they do not detail how this canbe done using BM.

The Single pattern category includes studies[P17, P35, P45] focusing on the define processand advocates more research addressing effective-ness and efficiency. Hacklin & Wallnöfer discusshow the business model is applied for strategicdecision making [P17]. They explore implicationsand limitations of using a business model asa “strategizing device” and how BM is forcingto formalize current activities and make implicitunderstandings. They propose future researchon the effectiveness of business: 1) deal withtechnical aspects how to systematically use BMto improve effectiveness; 2) to test the linguisticlegitimacy of various frameworks for BM; and3) improve the effectiveness of different repre-sentational modes of the business model to gainpragmatic validity. Buder & Felden evaluate theefficiency of representation and formalizationof value models (e3value and REA) to under-stand business models [P35]. They discuss theimpact of business processes on value creationand stress the importance of consistency betweenbusiness and process modeling. They find e3value


to be more effective and efficient in improvingthe linkage between BM and business processes.Doganova & Eyquem-Renault investigate thecommercialization of technology in the first yearsof new ventures and the dual role the businessmodel play [P45]. They argue the “performative”role as a demonstration and as a scale model thatgradually bring the company’s business into exis-tence. They also conclude that empirical findingsstill fail to provide convergent results regardingthe effectiveness of business models.

To summarize, the improvements associatedwith efficiency and effectiveness are neither sub-stantiated by empirical evidence nor groundedin empirical data. Given the diverse contextualsettings in the studies and the dependence ofthe BM approach, it remains an open questionwhether the application of any of the identifiedpractices results in increased or decreased effi-ciency or effectiveness for a company’s business.Any outcome variations may simply be a result offluctuating contextual or environmental factorsrather than the application of a BM methodor technique. Reaching reasonable coverage ofefficiency and effectiveness as external factorsrequire considering several measurable internalfactors. With a reasonable coverage of relevant in-ternal factors and taking into account contextualfactors, we most likely operate on tens of indepen-dent variables that need precise definition andmeasurement instruments. Given this, we arguethat none of the identified studies come near tothe required level of details to be able to considertheir measurements trustful (except for Andries& Debackere linking business model adaptationto a company’s performance via a survival ratemeasurement and other variables collected fromthe annual CorpTech directory [P42]).

We concur with Zott et al. that literature isdeveloping largely in silos, according to the phe-nomena of interest to the respective researcher[12]. We conclude that business model researchstill lacks a consolidated view of what a businessmodel is, while at the same time being forced toaddress more complexity (e.g., dynamic businessmodels, co-creation, collaboration, and ecosys-tems with a growing number of stakeholders).

6. Research synthesis

6.1. An analysis of business modelingtrends

We synthesized five main trends within our sur-veyed literature on BM:– Business models as the building blocks, and

the structure of a business model constructas a cornerstone for analyzing, planning andmanaging competitive and strategic advan-tages [P1, P2, P3, P4, P9, P13, P16, P19, P29,P32, P40, P41, P51]. Much research is putinto frameworks, methods, and tools but theeffectiveness and efficiency when integratingthis research into practical solutions still missempirical evidence.

– Locus of the company is shifting to the ecosys-tem resulting in an explosion of new roles andvalues that need consideration, as they areconnected to the value creation/capture logic[P2, P3, P4, P6, P21, P53, P57]. This trendmakes future research more complicated andtime consuming, given the lack of consoli-dated body knowledge on what a businessmodel is and how it can be represented tosupport experimentation and efficient infor-mation management.

– Experimentation and operationalization offlexible business models, to manage the speedof change fueled by technology innovation andthe digitalization of the value delivery [P1,P2, P9, P13, P15, P18, P49, P51]. We too,argue for a more cross-disciplinary agenda[57], as business modeling is facing the samechallenges as agile requirement engineeringand software development has been lookingat for the past 10 years trying to increasespeed and productivity [63].

– Changeability and modularity as ways tostrategically address all new roles and val-ues via choices to enable faster transitionsfrom strategy to execution (operationaliza-tion) [P1, P3, P5, P6, P23, P25, P26, P27].By systematically approaching the informa-tion management related to business models,changeability, and modularity, parts of the


practices for business modeling may becomeautomated as a solution to faster transitions.

– A growing need for multifaceted optimiza-tion of business models, as fueled by newroles and new values, as a contrast to thecurrently more dominant single dimension ofcost and revenue [P2, P7, P8, P9, P26, P53],often leading to sub-optimal solutions. Suchoptimization will drive a need for more so-phisticated decision support and higher levelsof automation in the governance of businessmodels and business model execution.We found no solutions or evidence related

to multifaceted optimization of business models,while at the same time multiple studies high-lighted the need for alignment of strategy and ex-ecution (daily operations). In combination withthe two related trends of experimentation andchangeability, we identified a common denomina-tor in governance, as a foundation for faster andmore transparent decision-support (for all rolesin their interactions). Also, we found no system-atic mechanism for organizational learning thatpotentially could minimize misunderstandingsand improve decisions, even though organiza-tional learning is important for successful BM[P9, P46].

We believe an important step towards suchmultifaceted optimization of business models liesin understanding how the business modeling prac-tice connects to governance for evaluating effec-tiveness and efficiency of a company. We, there-fore, propose CGM to facilitate the explorationof a governance framework for evaluating effec-tiveness (creating the right values) and efficiency(while using a minimum of resources).

6.2. A conceptual governance model(CGM) for exploring governanceand evaluating effectiveness andefficiency of BM

We synthesized CGM for exploring governanceand evaluating effectiveness and efficiency of BM.CGM is presented in Figure 5 and is inspiredby Zott and Amit’s work on business models asactivity systems that create value in transactions[5], and influenced by the theories of learning and

knowledge creation by Pask and Nonaka [20,64].CGM links governance to BM via the antecedents(H1, H2), the business model (H3), real-worldinteractions (creating value and learning), andconsequences (H4) as defined by Höflinger [7].It is a conceptualization of the diversity of theproblem of BM concerning value, effectiveness,and efficiency. We propose CGM be used forexploring experimentation in business modelingand designing a scalable IT solution. We believethe concept of “context frame” and intent-drivensystems [65] offers an exciting path forward andwill be elaborated as part of our future work.

Figure 5 illustrates how the BM practice fa-cilitates experimentation with a business modelthrough a set of interactions between actors in-volved in the define (P0) and execute (P1) pro-cesses. P0 and P1 are abstracted from the un-derlying phases of interaction and learning, asmentioned both by Nonaka (dialogue vs. prac-tice) and Pask (explaining vs. demonstrated un-derstanding). The processes exist in a context,influencing and influenced by the environmenton different abstraction levels (and each processcan also be seen as a representation of an activitysystem with its interdependent activities in linewith Zott and Amit’s work). Please note thatboth processes are highly context-specific, but al-ways executed in pairs (as interactions of activitysystems), e.g., context A = producing a strategy,context B = translating the same strategy intoan operationalized business model in products.Therefore, P0 and P1 interact in a highly recur-sive, non-linear, interactive manner.

Depending on the context, different tasks andactivities are executed (by sharing and modifyinginformation related to various parts of the com-pany’s strategies, organizations, policies, rules,and products in close relation to the ecosystem).Such context dependency is a critical and chal-lenging factor for a process-centric implemen-tation of activities since reuse easily becomescomplex, unpredictive, and slow [66].

Governance is an abstraction of goals, mea-surements, follow-up, rules, knowledge, and in-sights. Relationships r1 and r2 represent therelationship between governance of define andexecute processes and how governance is used


Figure 5. CGM, a conceptual governance model for exploring effectiveness and efficiencyin relation to BM with key relationships rx

to form an agreement (alignment of strategyand execution via goals, objectives, rules, mea-surements, and knowledge). r3 represents therelationship between the define and execute pro-cesses and how governance is involved in trackingdaily progress and facilitating alignment includ-ing change management (by executing in relationto the agreements established/updated via r1 andr2). r0 is used to manage the effectiveness andefficiency of the BM process, while r4 is usedto control the outcome of the business (modelexecution). Our future work aims to developthese relationships into software interface in ac-cordance with intent-driven systems [65].

Sustaining competitive advantage requiresconstant change [4]. Fundamental to this changeis to understand the difference (make an assess-ment) between the current position (means) andthe desired position (ends). Successful changeis thus a multifaceted function of alignment be-tween ends and means, maintained by timely ac-tions to modify ends and the means in response tothe environmental influences and consequences.The purpose of the relationships r0–r4 in Figure 5is to manage successful change systematically.However, common to all studies (with quotes ofpurpose, Appendix D) is a lack of details describ-ing the r1–r3 relationships and how the alignmentcan be achieved and maintained.

The importance of aligning the executionwith the strategy is specifically addressed by pa-

pers [P6, P32, P59] (without empirical results).Only Salgado et al. suggest solutions to how thatcould be done (methods and representation ofinformation) [P59]. Ballon proposes an analyticalframework and discuss how BM is interpreted as(re)configuration of control parameters (combina-tion of assets, vertical integration, customer own-ership, modularity, distribution of intelligence,interoperability) and value parameters (cost shar-ing model, revenue model, revenue sharing model,positioning, customer involvement, intendedvalue) [P6]. Osterwalder et al. advocate formaliza-tion of business models to create traceability be-tween business (the building plan) and execution(IS/IT systems) [P32]. Giessmann et al. extendOsterwalder et al.’s propositions to build a modelthat can analyze and compare business models,but their work does not address the issues ofaligning and daily execution of a business model[P55]. Salgado et al. also build on Osterwalder’sBMC and discuss how to generate a BMC frombusiness goals, rules, and processes, but do notfurther connect the results to the IS/IT realiza-tion and daily operations [P56]. They also discussthe alignment between business and IS/IT fromthe lens of business model artifacts, strategy andgoal modeling, as well as enterprise modeling[P59]. They formulate the primary challenge asAchieving alignment per se is not enough, orga-nizations have to reach the alignment state andmaintain it alongside its evolution.


The quotes for challenges and benefits (Ap-pendix D) also lack details describing the rela-tionships r1–r3 in Figure 5. Also, there are 62%more quotes than for purposes, which could be ex-plained by that benefits and challenges are oftenmore specific by nature than the correspondingpurposes. The identified quotes indicate a moreinhomogeneous nature regarding contextual set-tings, resulting in a scattered picture of benefitsand challenges. We speculate this is a result ofeach paper framing their conclusions with someform of benefits or challenges, rather than con-structing them from empirical findings.

The papers within the governance columnand assessment row (see Appendix D) presentimportant aspects of goals, rules, measurements,options, flexibility, and knowledge. However, theydo not propose solutions on how these concepts(with artifacts) should be represented or managedto create traceability to, and alignment with, thedefine and execute processes (via r1, r2, r3) inFigure 5.

Six papers [P2, P22, P29, P32, P36, P54]cover all three columns (define, execute, andgovernance), but no author elaborates on therelationships r1–r3 (alignment of define and ex-ecute processes using governance), see Table 3.Rohrbeck et al. study eight companies and discusshow collaborative BM can improve both defineand execute processes [P2]. They report improve-ments in four areas (dealing with uncertainty,finding creative solutions, facilitating a strategicdiscussion, and allowed to start the innovationplanning), but provide little details or empiricalevidence as to how well it works. Baden-Fuller &Morgan scan the literature and discuss businessmodels as models, describing their multivalentcharacter and the wide range of usage [P22]. Theyconclude Business models are not recipes or scien-tific models or scale and role models [. . . ] they playany – or all – these roles, often at the same time.Osterwalder et al. propose eight propositions forBM that need to be tested [P32]. Zott et al. intheir review six years later reveal that scholarsstill do not agree and that literature is developingin silos [P29]. Cortimiglia et al. explore, in a large

empirical-based investigation, the relationship be-tween the strategy making process and businessmodel innovation (BMI) [P36]. They summarizea large number of purposes found in literature,which also matches the improvement areas wehave identified, see section 5.1. Their findingsvalidate the role of business model innovation asa valuable tool for, and link, between strategy ex-ecution and operationalization. Meier & Bosslau,in their case study, propose an integrated designand engineering approach as an iterative learningprocess based on system dynamics. They concludethat further development of modeling and simu-lation that depicts the dynamics and flexibility inthe whole life-cycle is one of the key challenges forbusiness model research (in a context of industrialproduct service systems) [P54].

7. Implications for researchand practitioners

The results suggest that business model (andBM) is a diverse research area which would ben-efit from more aggregation efforts [P29, P40, P3,P9] on how business models could address thevast set of purposes and practices for BM, andwhat effects BM have on effectiveness and effi-ciency of a company. More work is needed toconsolidate these different angles of the businessmodel construct into a scalable, practically use-ful representations that will facilitate innovation,experimentation, and operationalization of thebusiness model. The lack of coherence is morerecently investigated by Massa et al. [67], as theyidentify possible reasons for the current lack ofagreement in literature as terms and conceptsslowly morph over time.

In the same vein (seen from a practitioners’side), Gartner7 in 2014 points out that digitalbusiness should not be considered an IT programand should instead become an enterprise mindsetand lingua franca, with digital expertise spreadacross the enterprise and value ecosystem.

Our results confirms the above and highlighta challenging issue for effectively and efficiently

7Gartner identifies six key steps to build a successful digital business, https://www.gartner.com/newsroom/id/2745517

https://www.gartner.com/newsroom/id/2745517

https://www.gartner.com/newsroom/id/2745517


defining contexts to improve understanding andcommunication in BM literature. We also notea potentially strong correlation between flexibil-ity, effectiveness, and efficiency (all 13 papersaddressing RQ2 also address aspects of flexibilityand variability in the realization, IC2 and IC3,see Table 2).

We recommend the following topics to beadded to a cross-disciplinary agenda for BM:– Further exploring how contextual informa-

tion in the business model construct could besystematically represented, structured, andstored. The improved representation of con-textual information is going to increase effec-tiveness and efficiency when creating, mod-ifying, and deleting information needed totransform strategies into tactics and dailyexecution, e.g., facilitating business modelchoices, including a residual set of choicesrelated to tactics, and deciding on choicescontrolling daily interactions between stake-holders (as controlled by a set of configura-tion parameters and rules in software appli-cations). A business model construct mustsupport collaborative and role-based interac-tion, including exchange and interpretation ofcontextual information, scalable to thousandsof actors, and across corporate borders. Webelieve intent-driven systems [65] could bea way forward for this purpose.

– Connecting the BM practice with LearningTheory would help to create a model thatcan help explain: 1) how value creation andstakeholder motivation is derived from, andconnected to, daily interactions; 2) how dailyinteractions, in combination with organiza-tional learning, shape the transformation ofstrategy into execution; and 3) how organiza-tional learning influences the process of BM.These aspects become increasingly importantsince experimentation with value co-creationand business models are gaining interests [P2,P9, P13, P18]. This implies BM to be in-volved, not only in strategy and planning butalso in the operationalization and follow-up ofthe business model, as the focus of a businessmodel is shifting beyond the company bordersinto the ecosystem.

The implications for industry originatemainly from the lack of tangible results linkingefficient BM to efficient and effective businesses.We recommend managers to investigate and buildawareness of the following aspects:– Systematically converting experience into

knowledge will help the organization iden-tifying and verbalizing (new) values andmotivators relevant to the business. Inves-tigate how to incorporate organizationallearning (OL) [68] into everyday practicesand business processes to support experi-mentation with business models, e.g., whatis the current level of OL? How is OLincorporated into important business pro-cesses? Which roles are currently not in-volved in structured OL? How is OL re-lated to the fulfillment of goals, an organiza-tion’s creativity and motivation, and incen-tives?

– Critical components in any SIPD businessmodel are concepts such as value co-creation,collaborative value networks, and acquiringresources beyond the control of the com-pany (i.e., creating an ecosystem of part-ners and customers). How to prepare a com-pany’s staff and products to these concepts?How do you facilitate similar activities foryour partners? These ideas will affect theproducts and offerings but also fundamen-tally change most aspects of a company’spolicies and business processes includingincentive structures and management sys-tems (e.g., sharing of information internally/externally and risk management). We be-lieve the introduction of a value vocabu-lary, to facilitate more precise understand-ing and definitions of business-critical con-cepts, is a concrete and valuable first step,e.g., SVM [48].

– What factors hinder business model experi-mentation? What level of business flexibilityis required (and used)? How is that flexibilityimplemented in the products, organization,business processes, and management systems?The value creation process is highly inter-dependent and not well suited for isolatedpractices [P14, P15, P30]. Business modeling


could become a tool to bridge these practices[P2] and SIPD companies should not see soft-ware architectures and methods as costs. It’sa significant investment that facilitates exper-imentation while adding to the value creation.Such investments in business flexibility willbecome a crucial source of innovation andan enabler for automating business processes,resulting in an increased efficiency and com-petitive advantage.

– A governance mechanism is a critical ele-ment to build a commitment to experimenta-tion and the development of the appropriatebusiness flexibility. The mechanism shouldsupport multi-contextual governance views,maintaining traceability between all choices(strategical, tactical, and operational) andthe views must be based on data from differ-ent contextual situations (narrative, planning,development, daily operational tasks, phaseout, etc.) [65].

8. Conclusions

This systematic literature review explores thepurpose of business modeling and its impact oneffectiveness and efficiency of a company’s busi-ness. Most companies invest in business modeling,but remain uncertain whether their investmentsallow them to change and adapt their businessfast enough.

Our results show that the reported benefitsare unsubstantiated or claimed with limited em-pirical evidence and the challenges are dispersed.The most common challenge is how to deal withthe dynamics of business models, and most of thequotes on challenges relate to the non-existingsolutions for governance (representation, simu-lation, decision-support, and feedback) of theproposed frameworks and methods.

The improvements associated with efficiencyand effectiveness of BM are neither substantiatedby empirical evidence nor grounded in empiricaldata. Given the diverse contextual settings in thestudies and the dependence of the BM approach,

it remains an open question whether the applica-tion of any of the identified practices results inincreased or decreased efficiency or effectivenessfor a company’s business. Any outcome variationsmay simply be a result of fluctuating contextualor environmental factors rather than the appli-cation of a BM method or technique.

We concur with Zott et al. that literature isdeveloping largely in silos, according to the phe-nomena of interest to the respective researcher[12]. Since the influential work by Osterwalderet al. on business models [9], which later gaineda lot of interest among practitioners8, researchersare still reporting that business models and BMis a diverse research area missing an agreed defi-nition of business model. It is an area that wouldbenefit from more aggregated cross-disciplinaryresearch results [57,67].

Supported by our results, we argue that:– Related to RQ1, what makes business model

research results challenging to analyze, com-pare, and combine is the lack of a systematicapproach in describing the contextual infor-mation used to define the context for a spe-cific business model construct and businessmodeling practice. The lack of systematic con-textual information leads to inefficient com-munication, knowledge creation, and organi-zational learning, which affects the quality ofdecisions (on all levels). A consequence forbusiness modeling is misalignment betweenthe business model and its realization, whichnegatively affects the value creation (effec-tiveness) and the efficiency. By improving theinformation management parts of these pro-cesses, tasks may become automated, open-ing up for new ways of specifying and vi-sualizing strategies, goals, and operationalconsequences, as related to effectiveness andefficiency.

– Related to RQ2, we conclude that governanceis going to gain importance, as it must effec-tively support a chain of continuous adap-tations and learning (experimenting). Suchgovernance can enforce a continuous (businessmodel) design aligned with the continuous

8Originally called the Business Model Generator in 2010, now changed into a commercial product https://strategyzer.com/canvas.

https://strategyzer.com/canvas

https://strategyzer.com/canvas


(business model) execution. We further ar-gue that governance is the primary challengefor business modeling, and that (continuous)business modeling can be used (via gover-nance) to effectively and efficiently cope withchange, by connecting the definition of strat-egy to the execution of operations in dailydecisions and activities as depicted in Fig-ure 5.

– By combining above conclusions, that thelack of a rigorous, scalable, context-dependent(software and IT) representation of the busi-ness model, in combination with efficient gov-ernance mechanisms (to manage needed flex-ibility), are currently significant obstacles forprogressing the research area and support-ing the industry in managing innovation inco-creation-driven (software-intensive) busi-ness ecosystems.We, therefore, believe our conceptual gov-

ernance model is a significant step to exploreand identify how the business modeling practicecould become an integrated cornerstone in a moreeffective and efficient software-intensive productdevelopment enterprise. Our conceptual gover-nance model can facilitate the creation a commonbusiness model construct including mechanismsto support effective and efficient governance withvalue-based decision-support for all affected rolesand stakeholders.

Also, we believe our extensive, cross-disci-plinary review of the business model litera-ture, seen from the perspective of software andsoftware-intensive products, is a valuable contri-bution for the Software Engineering communitywhen trying to address the digitalization’s effectson software engineering and software productdevelopment.

Our next steps in our research towards ef-ficient and effective business modeling are touse our proposed conceptual model to identifyessential characteristics of a governance frame-work and a scalable business model construct, asrequired to facilitates effective and efficient oper-ationalization of a business model. We will alsoverify the conceptual model with practitionersto ensure that our results can be disseminatedby industry.

Acknowledgment

We are grateful for the constructive and helpfulcomments on early drafts received from Prof.Lars Bengtsson, LTH, Sweden. This work hasbeen supported by the Professional Licentiateof Engineering (PLEng) Pilot Run 2014–2018 incooperation with Ericsson AB. This work is alsosupported by the IKNOWDM project (20150033)from the Knowledge Foundation in Sweden.

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Appendix A. Selected articles

Table A lists all the articles selected through thesnowballing methodology. It contains Paper ID,author/bibliographic reference, plus extracteddata for rigor and relevance factors (EP3), pa-per content (EP4), and the number of topics(RQ1+RQ2+IC2+IC3)9 addressed by the pa-per. A detailed description of EP3 (including

calculation of scores) and EP4 are found in theAppendix C while details of IC1–IC3 are foundin Appendix B.

In the main article we use the notation [PaperID,. . . ] to indicate a reference to one or more ofthe study’s selected papers when we specificallytalk about a result or an synthesis thereof. Pleasenote that the start set consists of P1–P10.

Table A. Selected papers including extracted properties

Paper Rigor (EP3) Relevance (EP3) Content No. ofID Authors/Ref Year C SD V C Sc Su RM EP4 RQ+IC

P1 Woodard et al. [69] 2013 1 1 1 1 1 1 1 2 4P2 Rohrbeck et al. [28] 2013 0.5 1 0 1 0 1 1 1 3P3 Reim et al. [26] 2013 0.5 0.5 0 0 0 0 0 2 3P4 Hackney et al. [70] 2004 0.5 0 0 1 1 0 0 3 2P5 Chew [71] 2014 1 0 0 1 0 0 0 2 4P6 Ballon [33] 2007 0 0 0 1 0 0 0 1 3P7 Loss & Crave [72] 2011 0 0 0 1 0 0 0 2 3P8 Romero & Molina [73] 2011 0 0 0 0 0 0 0 3 3P9 Höflinger [7] 2014 0.5 1 0 0 0 0 0 2 3P10 Goel et al. [74] 2009 0.5 0 0.5 0 0 0 0 3 3P12 Casadesus-Masanell & Ricart [4] 2010 0 0 0 1 0 1 0 3 3P13 Chesbrough [30] 2010 0 0 0 1 0 0 0 2 3P14 Demil & Lecocq [75] 2010 1 0 0.5 0 0 1 0 2 2P15 Doz & Kosonen [35] 2010 0 0 0 0 0 0 0 1 2P16 Dubosson-Torbay et al. [76] 2002 0 0 0 0 0 0 0 2 2P17 Hacklin & Wallnöfer [54] 2012 1 0.5 0 1 1 1 1 1 3P18 McGrath [31] 2010 0 0 0 0 0 0 0 1 3P19 Richardson [77] 2008 0 0 0 0 0 0 0 2 3P20 Storbacka & Nenonen [78] 2011 1 1 1 1 1 1 1 2 2P21 Zott & Amit [5] 2010 0 0 0 1 0 0 0 2 2P22 Baden-Fuller & Morgan [27] 2010 0 0 0 0 0 0 0 2 3P23 Gao et al. [79] 2011 0 0 0 1 0 1 0 3 2P24 Kindström [80] 2010 1 1 0.5 1 1 1 1 2 4P25 Meier & Massberg [81] 2004 0 0 0 0 0 0 0 3 2P26 Meier et al. [46] 2010 0 0 0 1 0 1 0 3 3P27 Richter et al. [37] 2010 0 0 0 0 0 0 0 2 2P28 Schuh et al. [82] 2009 0 0 0 0 0 0 0 3 1P29 Zott et al. [12] 2011 0.5 1 1 0 0 0 0 2 4P30 Amit & Zott [83] 2001 1 1 1 1 1 1 1 3 2P31 Baden-Fuller & Haefliger [10] 2013 0.5 0 0 0 0 0 0 3 3P32 Osterwalder et al. [9] 2005 0 0 0 0 0 0 0 2 3P33 Al-Debei [23] 2010 0.5 0 0 1 1 1 1 2 3P34 Bouwman [84] 2006 0 0 0 0 0 1 0 3 3P35 Buder &Felden [17] 2012 1 1 1 0 1 0 0 1 4P36 Cortimiglia et al. [85] 2015 1 1 1 1 1 1 1 1 2P37 Ghezzi [86] 2013 0.5 0.5 0.5 1 1 1 1 1 4

9IC1–IC3 are topic-oriented while IC4 and IC5 are related to rigor and relevance.


Paper Rigor (EP3) Relevance (EP3) Content No. ofID Authors/Ref Year C SD V C Sc Su RM EP4 RQ+IC

P38 Ghezzi [87] 2012 0.5 0 0 1 1 1 1 3 2P39 Haaker et al. [22] 2004 0.5 0 1 1 1 1 1 2 2P40 Krumeich et al. [11] 2012 0 0.5 0.5 0 0 0 0 2 2P41 Zolnowski & Böhmann [44] 2011 0.5 0.5 0 0 0 0 0 1 2P42 Andries & Debackere [88] 2007 1 1 0.5 1 1 1 1 3 2P43 Björkdahl [47] 2009 0.5 0.5 0.5 1 1 1 1 3 2P44 Casadesus-Masanell & Llanes [42] 2011 1 0 0 0 0 0 0 3 2P45 Doganova & Eyquem-Renault [29] 2009 0.5 0.5 0 1 1 1 1 2 4P46 Mason & Leek [89] 2008 0.5 0.5 0 1 1 1 1 3 2P48 Lindström [90] 2014 0.5 0.5 1 1 1 1 1 3 2P49 Eurich et al. [6] 2014 0.5 0.5 0 1 1 1 1 1 3P50 Ning et al. [91] 2011 0.5 0.5 0 1 1 0 0 3 0P51 Dmitriev et al. [92] 2014 1 1 1 1 1 1 1 1 2P52 Schneider & Spieth [36] 2014 0.5 0.5 0.5 1 0 0 1 1 3P53 Short et al. [93] 2013 0 0 0 1 1 0 1 1 2P54 Meier & Boßlau [46] 2013 0.5 0 0 1 1 1 1 1 4P55 Giessmann et al. [58] 2013 0.5 0 0.5 1 0 0 0 3 3P56 Salgado et al. [59] 2014 0.5 0 0 1 1 1 1 1 3P57 Kim et al. [94] 2008 1 0 0 0 0 0 0 3 2P58 Mason & Mouzas [95] 2012 1 1 1 1 1 1 1 3 2P59 Salgado et al. [34] 2014 0 0 0 0 0 0 1 3 2

Appendix B. Inclusion and exclusioncriteria

To identify literature related to our research ques-tions, we developed the Inclusion criteria (IC) andExclusion criteria (EC) listed in Table B. These cri-teria allow us to explore why BM is used, how it isapplied, and what solutions currently exist. Since ourresearch topic covers multiple research disciplines, wedecided to address the RQs by designing the IC aswide as possible, to give us a large variety of articlesdiscussing BM (IC1) in any relationship to effective-ness and efficiency. To evaluate BM efficiency, it isimportant to connect the business strategy via thebusiness model to the execution of the business modelwith a traceability to daily operations and results. Soto understand if business modeling enables effective-ness and efficiency, we want to know how a businessmodel can be operationalized by developing the righttype of flexibility (variability in the realization, IC3)matching all desired strategical and tactical choices(business flexibility, IC2).

Business modeling allows an organization to iden-tify and prioritize changes to current business op-erations (content, activities, and governance). Thischange is continuously translated into a realization ofthe business model, through experimentation or oth-erwise, by understanding how the desired flexibilitycan be operationalized using modularity in design and

software-based systems to support content, activities(all stakeholders, e.g., internal organization, partners,suppliers, and customers) and governance.

Effectiveness and efficiency should be evaluatedfrom the gap between all strategic and tactical choices,in combination with how the organization (and sup-porting software) utilize the remaining flexibility tocreate satisfied customers in everyday transactions.The dilemma of not only implementing the rightflexibility (supporting the needed business options)but also implementing it efficiently, is key to success,i.e., the right level of variability in the realizationcombined with the appropriate changeability in therealization to facilitate experimentation with the op-erationalized business model.

The selection critera was based on IC1 AND (IC2OR IC3 OR IC4 OR IC5) to achieve a broad selectionof papers as possible. If only the term Business modelwere used (and not specifically Business modeling),the paper could still be a candidate if it referred to ac-tivities related to creating, maintaining, or otherwiseusing a business model.

Appendix C. Data Extractionproperties

Table C lists the data extraction properties usedfor this study and maps their relevance to each RQ.


Properties EP1-EP4 are evaluated per paper andused to analyze the relevance to industry for eachpaper’s contribution. Properties EP5-EP9 use opencoding and the extracted data was thematically andnarratively analyzed.

Property EP1 and EP2 are subset of propertyEP3 (Rigor & Relevance) where property EP2 cate-gories the paper’s context. We extend the definition ofContext (EP3 [96]), by adding (large-scale) Softwareintensive industry. The relevance parameter (EP3),we coded with binary weights (originally proposed asplain sum of 0 or 1), allowing us to visualize the im-pact of different relevance aspects. The weights wereguided by RQ1, hence setting our priority: Industry(8), Scale (4), Subjects (2) and Research method (1),e.g. a value of 9 or higher would represent anythingin “industry” with at least one additional relevanceaspect met. Originally the Relevance element of prop-erty EP3 focus on the paper’s context in relation toindustry so we added property EP4 (Paper content)to map the relevance of each paper’s content relatedto answering the RQs.

EP5 corresponds to our inclusion criteria (IC).EP6 was used to look for patterns on the businessmodel construct as to describe what it is, why itis important and how it is used. This is importantsince the topic of BM is wide and lacks a clear defini-tion. EP7-EP9 was used to understand the contextfor effectiveness and efficiency as related to businessmodeling.

Appendix D. Quotes of purpose,benefit and challenges

Table D lists the quotes of purposes, benefits, andchallenges for business models and business modeling,extracted from the selected studies (see Appendix Afor paper references). All quotes have been categorizedinto common areas (first column), and then listed un-der respective primary context they are found in. Weuse prefix notation (+) for benefit, (−) for challenge,and [PID] for the paper reference.

Table B. Inclusion and exclusion criteria

Criteria Evaluate (=Yes) Reasoning

EC1 Exclude if not written in English Must be able to read and understand to evaluateEC2 Exclude if not peer-reviewed Basic quality assurance of paperEC3 Exclude if duplicated Snowballing will give many duplicates

IC1 Does the abstract, introduction,conclusions (or full text if needed)mention purposes, benefits orchallenges (PBC) for businessmodeling?

Papers must identify real problems and issues related tobusiness model, business modeling or business modelinnovation.

IC2 Does the text mention aspects ofbusiness flexibility (BF)?

BM is becoming increasingly complex due to growingbusiness ecosystems and the digitalization of the valuedelivery, which both introduce a need for variability inthe offering. Offering services on top of products are oneexample to address BF.

IC3 Does the text mention aspects ofvariability in the realization (VR)?

Planning a business model is not enough. It needs to beefficiently realized as well, so the business flexibilityneeds to be matched with a variability in the realizationof the business model. Offering Software Product lines(SPL) or Product Service Systems (PSS) are examplesof addressing VR.

IC4 Is it an empirical study? We want to investigate how business models are used inpractice, and not only in theory. Empirical is done in anindustrial context, no student work, no proof of concept,no examples even if they are “based on real data”

IC5 Is it referring to a SIPD context? The realization of business models is highly dependenton software due to the digitalization of the valuedelivery. This opens up new opportunities for valuecapture (and value creation) in the business ecosystems.


Table C. Data extraction properties

Id Evaluate How RQ mapping

EP1 Research methods Action research, case study, conceptual analysis, designscience research, experiment, interview, literature review,not stated, other

relevance of paper

EP2 Paper context SW intensive, industry, general (e.g. literature review),non-industry (in priority order)

RQ1 and relevance

EP3 Rigor & relevanceof the paper

Detailed rubric definitions per aspect [96]Rigor: Context is describedRigor: study design is describedRigor: validity is discussedEach rigor aspect measurement: strong description (1),medium description (0.5), and weak description (0)

Relevance: context (weight=8), i.e. in industrial settingRelevance: scale (weight=4), i.e. realistic size and indus-trial scaleRelevance: subjects (weight=2), i.e. industry professionalsRelevance: research method (weight=1)Each relevance aspect measurement: contribute to rele-vance (1), do not contribute to relevance (0)

Overview and rele-vance

EP4 The relevance ofthe paper contentin respect to busi-ness modeling.

Coded 1-3: (1) business modeling; the paper discuss specif-ically the process of modeling your business(2) business model; the paper mainly focus on the businessmodel and discuss how different aspects of the Businessmodel constructs are developed(3) Other; it only refers to a specific business model(s),or discuss specific instances thereof, or a topic relatedto business model (e.g. flexibility); therefore of minimalsignificance to our study

RQ1

EP5 IC1-IC3 Use ATLAS TI to extract related quotes for each RQ. RQ1, RQ2EP6 Business element

contextUse ATLAS TI to extract related quotes referring to apart of the business model construct, what it is, why it isimportant and how it is used and relates to other parts.

RQ1

EP7 Practice/technique Use ATLAS TI to extract quotes referring to a practiceor technique presented, described or used.

RQ1, RQ2

EP8 Measurement per-spective

Use ATLAS TI to extract quotes related to– Product view (how well is the value created)– Process view (how efficient have you organized the valueflow)– Resource view (how well is the resource utilized andadapted for the needed task)– Project view (how efficient is the goal fulfilment)– Relationship view (how effective is the communication)

RQ2

EP9 Success indicatorand metric

Use ATLAS TI to extract related quotes RQ2


Table D. Quotes on purpose, benefits and challenges for BM

Commonareas

Strategy & planning (define) Daily operations (execute) Governance & communication

Valuecreation,valuecapture

Conceptual discussion andvisualization of valuecreation/capture [P2]Articulate Value proposition[P7], [P13], [P35]Identify a market segmentand value chain [P7], [P13],[P20]Appropriate value fromtechnology [P36](+) depicts the logic forvalue creation/capture [P17](+) fosters innovation andincreases readiness forfuture [P32](+) rigorously describes andanalyses business withsystem dynamics [P36](−) hard managing tensionbetween value creation andvalue capture (trade-offsmonetization) [P5](−) hard managing serviceflexibility (segmentation,QoS) [P5], [P24](−) ensure consistent serviceexperience (multi-channels)[P5](−) a total value needconsideration (not onlyfinancial) [P53]

Reconfiguration of roles andrelationships [P8], [P20]Determining the logic forvalue [P30](+) captures how resourcestransforms intocustomerswillingness to payfor value [P18](−) service vs. productcentric create conflicts,balancing is difficult [P1],[P24](−) low effectiveness(customer experience) ofvalue co-creation(organization/customer) [P5](−) it is difficult toincorporate closer customerinteraction [P24](−) how to acquire resourcesin value chain not previouslyavailable in-house [P24]

Describe and classify businesses [P32],[P22]Meeting customerś needs [P58]Compare value creation approaches [P32](+) facilitates strategic discussion andfinding creative solutions [P2](+) it is a structural template formapping existing value logic [P17](+) reduces imitability, create sustainableadvantage [P24](+) creates novel approach for usingservices in value creation [P41](+) it is explicative and predictive powerto value creation [P45](+) helps calculate technology value toinvestors, customers, partners [P45](−) complex coordination for ecosystemcollaboration [P2](−) negatively influences optimal valueco-creation in aligned processes [P5](−) new value (co-)creation focus onrelationship-centric aspects [P7](−) difficulty in identifying marketopportunities due to changing customerneeds [P9](−) difficulty to effectively communicate(articulate, visualize) emerging valueproposition [P24](−) hard to analyse business process vs.value activities [P35](−) many frameworks has many deficitsconcerning consistency and valueactivities [P35](−) lacks a quantitative way to conveyvalue and no sales model for perceivedvalue [P48](−) difficult to visualize value forintegrated offers [P48](−) BM has a dual nature conceptualizingvalue and organizing for that value (indifferent life cycles) [P51]


Commonareas


Cost,revenue,profit

Estimate cost/revenuepotential [P7](+) depicts actual structuresfor a company to profit frombusiness [P9](+) experiment with costbefore investing [P18](−) “black-hole” investment[P18](−) incorporaterequirements for leanconsumption and achievethe objectives of serviceprofit chain [P5](−) develop technologyinnovations in an adaptiveprocess (trial-and-error)with cost as main cause forreadjustments [P51]

(−) adaptation toenvironment bytrial-and-error [P51](−) amount of humanresources needed formodeling [P56](−) new revenue streamsdriven primarily bycustomer perceived valueinstead of internal cost [P24]

Incentives to engage in and controloperations [P20](−) maintain accurate definition ofownership conditions in a collaborativebusiness model, and revenue modelconsidering risk distribution [P54](−) maintain a new value chain rewardsystem [P24]

Mind-set,Knowl-edge

Experimenting [P2], [P22],[P49]Shift companyś boundaries[29]Exploit businessopportunity [P22], [P29]Foster Innovation [P32]Increase knowledge [P29](+) focus beyondcompany-centric focus [P17](+) shifts focus from WHATresources to HOW to usethem [P18](+) BMI enables strategicrenewal [P36](−) turns shared meaninginto identity lock-ins [P17](−) resistance to change[P17](−) plan for“experimentation andlearning” in establishedcompanies [P18](−) systematic servitization(product to service shift)[P24](−) hard to define businessrequirements (lack ofinformation and specificdetails) [P56]

Enhance creativity, unlockbarriers of innovation [P2]Build trust [P2]Increase readiness viaportfolios and simulation[P9], [P32]Build knowledge [P22](+) uses of mixed techniquesbetween Business and ITimproved communicationand IT development [P56](−) how to achieveorganizational and customerlearningś incorporated intoiterative design [P5]

Mediating, facilitating and sharingstrategic discourse [P17], [P36]Address lack of knowledge [P45], [P22](+) unlocks barriers of innovation +building trust [P2](+) breaks cognitive structures and act ascommunicative, mediating device forshared meaning and commitments [P17],[P32](+) improves understanding, languageand legitimacy [P17], [P32](+) formalization forces implicitunderstanding becoming explicit (movestrategy into execution) [P17](−) lack of formality and analystdependency with high skills [P56](+) promotes outside in view on customervalue [P18](+) provides early warning for threatenedBM via analysing dynamism ofcompletive advantage [P18](+) highlights consistency strategy andBM building blocks [P24](+) provides new insights (externalize,map and store knowledge) [P32](+) fosters systematic BMI [P32](+) unambiguously defines dimensions,properties and semantics [P33](+) visualization improves understanding[P32], [P56](+) helps define goals [P32](+) educates decision-makers for informeddecisions, goals and requirementengineering [P32]


Commonareas


Means Innovation and technologymanagement [P29]Plan and design businesslogic [P32]Understand complexinterplay [P31]Adopt servitization tofurther enhance globalcompetiveness [P54](+) Preparesimplementation (identifyingjoint activities with priorityand validating the businessmodel) [P2](+) Helps to build betterstrategies (e-business) [P32](−) Business model designrequires better integrationwith strategy analysis [P37](−) Difficult to besystematic (too slow, toodetailed, iterative) [P17](−) limited empiricalvalidation [P17](−) provides good insightsbut lacks support where tostart investing to reachfuture business [P18](−) capture customerśreaction to new technology[P5](−) hard to effectivelybalancing (conflicting)requirements (user anddesign) and strategicinterests (of partners) [P39](−) tools conceptual,complicated and too timeconsuming (for networkcentric BM) [P53](−) paradigm shift businessactivities and consumptionpatterns must be alignedwith environmental andsocial objectives [P53]

Change and implementbusiness logic (and businessprocess execution) [P17],[P32]Realize strategic tasks [P9]Support resource fluidity[P15]Commercialize ideas &technology [P29](+) better requirementengineering [P32](+) facilitates and improveschoices in IS/IT [P32](−) difficult to mobilize andalign available resources(not only internal but alsoextending external base) intime [P9], [P15], [P24](−) integration, agility andchange [P10](−) barriers to changebusiness model are realprocesses and tools are notgood enough [P13](−) a structured servicedevelopment processconnected to the businessmodel [P24]

Alignment of strategy, businessorganization and technology [P32]Manage flexibility and increase changecapability [P58](+) improves measuring, observing andcomparing business logic [P32](+) improves design of sustainablebusiness models [P32](+) improves alignment of strategy,organization and technology andintegration business IS/IT domains [P32](+) BM may enable strategy executionand how operational choices affectcompanyś performance [P37](+) helps to react to environment changedue to strategic flexibility and dynamiccapabilities [P52](−) hard to reach and maintain alignmentof business model and information systemmodel [P59](−) value co-creation is a hardcooperative process (speed, coordination,compromise) [P8](−) how to industrialize large-scale serviceofferings [P24](−) how to avoid isolated change(relationships, value, dynamic portfolio)[P24](−) hard to visualize, document and sharebasic elements due to relationships andspeed of change [P26], [P32](−) hard to achieve consistency betweenBM and BPM and achieve realimprovements with BPM [P35](−) lack of appropriate methods andtooling for BM integrated with BPM[P35](−) BM design requires better integrationwith strategy analysis models [P37](−) discovery of goals and rules nocommon process for elicitation [P56]

Ends Describe position ofcompany in value network[P7], [P13], [P29]Formulate competitivestrategy with goals andobjectives [P19], [P37]Act as receipt for thebusiness [P22]

Operationalize strategy[P36], [P37]

Alignment of strategy, businessorganization and technology [P32]Act as a scale model and role model forcharacterization of similarities anddefinition of difference [P22](+) facilitates and improves choices in ISrole and structure [P32]


Commonareas


Assessment Deal with uncertainty [P2],[P52], [P54]Holistic picture of futurestate [P2], [P32]Explain strategic issues(value creation, competitiveadvantage, companyperformance etc.) [P36],[P29]Support Leadership unity[P15]Explore and designpromising businessconcepts/ideas [P32], [P36],[P41]Strategy and business modelinnovation [P17], [P36],[P52], [P53](+) facilitates strategicdiscussion with sharedinsights to barriers/drivers(visual + levels of details)[P2](+) facilitates interaction tocreate strategic options andshare mediate strategicdiscourse [P17](+) help to betterunderstand the business andits important parts [P24](+) helps to improveplanning, change andimplementation (withknowledge and facilitatechoice of indicators) [P32](−) difficult managingdynamics (agility,adaptability, planning,decision) for alignment toenvironment and otherorganizations [P2], [P5],[P7], [P9], [P36](−) different methods orpatterns not aligned, noguidance how to obtain finaldesign [P49](−) neglects the relevancefor environment – focus onmodel-internal consistency[P49]

Alignment of control andvalue parameters [P6]Mapping of business roles orinteractions onto technicalmodules, interfaces, etc. [P6]Analyse functioning of anorganization [P32]Describe use of informationtechnology [P32]Improve the Business-IS/ITdialogue [P32], [P56](+) managing a businessmodel portfolio can lead toflexibility in re-organizingresources [P9](+) low-risk experiments viasimulation [P32](−) balancing act betweencustomer, revenue, cost,functionality (e.g. localadaptation vs. sw platform)[P1](−) mutual alignmentbetweensteps/organizations/customerswhen performed iterativelyand holistically [P5](−) how to matchconsequences ofenvironmental changes ontocompany with best fit [P9](−) a continuously learningbusiness modelexperimentation [P13](−) business model change(hard decision, riskyorganizational adjustments,and collective commitment)[P15](−) efficient management ofinformation (explore vs.create collectiveunderstanding) is difficult[P45]

Force decisions [P2]Analyse Business model fit [P49]Bridge static view for change andperformance over time [P14]Computerize DDS for better design,critique and simulation of new BMs [P32]Understand how technology is convertedinto market outcome [P29], [P31]Provide contextual information [P35]Identification of critical success factorsand investigate performance [P41]Proof, persuasion, comparison andbenchmarking [P45], [P55](+) creates common language, sharedpriority and forces decisions [P2](+) improves dealing with uncertainty(reduction by sharing, turn into advantage,enhance understanding of barriers) [P2](−) difficult to deal with uncertainty,complexity and dynamism [P54](+) facilitates brainstorming (today andfuture) and integrative (no theory bias)[P17](+) helps reducing complexity (visual)[P32](+) improves mutual understandingBusiness and IT domains [P32](+) facilities identification of keyindicators to follow execution of plan[P32](−) difficulty in reliable monitoring of keyindicators [P54](+) BM as “scale model” demonstratesfeasibility and worth to partners [P45](−) achieve joint strategy when decisionscreate cross-functional/divisional conflicts[P5](−) align social, organization, andtechnology (due to richness and change ofknowledge economy) [P7](−) difficult to choose from massiveresults regarding BM designexperimentation [P18](−) hard to identify threats to BM intime [P18](−) managed different abstraction levelsand get the details right in execution[P19], [P21](−) requires decision-making on multipleparameters of activity systems [P21](−) BM has a dual nature (instance vs.classification) [P22](−) hard to overcome resistance to andawareness of need to change [P52](−) over-estimate/false impression of yourability to change [P52]

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