RFID Technology in the Indian Retail Sector

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    RFID Technology in the Indian Retail Sector

    There is growing interest and investment in the use of radio frequency identification

    (RFID) technology as a means of greater visibility in supply chains, leading to improvedinventory management through improved customer and sales information in retail chains.

    Retailing is emerging as a technology-intensive industry, and China and India are

    emerging as potential major retail countries. Given the growing importance of the retail business and application of information and communications technologies (ICTs),

    particularly RFID, it is important to understand RFID technology per se and its likely

    benefits in the retail sector in a developing country like India, where even bar codes arestill not ubiquitous. We discuss RFID technology and its potential scope in the retail

    sector briefly, and the Indian retail sector in considerable detail. Thereafter, we discuss

    the findings of field case studies of three upcoming retail chains, all of which are workingon identifying the possibility of switching to RFID from bar codes in the coming future.We attempt to understand how RFID application is likely to impact their operations and

    supply chains. We develop an adoption and implementation barrier framework and find

    out where the three retail chains stand in this framework. Finally, we suggest managerialrecommendations, as well as directions for future work.

    Information Technology in Indias real retail sector

    October 26, 2007 at 5:06 pm | Posted in Accounting, International business | Leave a

    comment

    Having been in IT industry and being based in India for a good part of the last decade we

    have now got used to relatives and friends with retail outlets small and big asking us

    about computers and software and our advise on how to go about them. Most of the

    questions relate to accounting perhaps acc101 can be a place where software for

    accounting and related items are discussed.

    A question that has been generally asked is whether they have to purchase tally, the most

    popular accounting package in India or ask their relative or somebody in their

    neighborhood who has done a course from NIIT or similar training institutes to help them

    create a new software to be used in their shops. We have not had an opportunity to check

    which of the two is a better option. Our experience in developing, implementing, selling

    http://accounting101.wordpress.com/2007/10/26/information-technology-in-india%E2%80%99s-real-retail-sector/http://accounting101.wordpress.com/2007/10/26/information-technology-in-india%E2%80%99s-real-retail-sector/http://en.wordpress.com/tag/accounting/http://en.wordpress.com/tag/international-business/http://accounting101.wordpress.com/2007/10/26/information-technology-in-india%E2%80%99s-real-retail-sector/#respondhttp://accounting101.wordpress.com/2007/10/26/information-technology-in-india%E2%80%99s-real-retail-sector/#respondhttp://en.wordpress.com/tag/accounting/http://en.wordpress.com/tag/international-business/http://accounting101.wordpress.com/2007/10/26/information-technology-in-india%E2%80%99s-real-retail-sector/#respondhttp://accounting101.wordpress.com/2007/10/26/information-technology-in-india%E2%80%99s-real-retail-sector/#respondhttp://accounting101.wordpress.com/2007/10/26/information-technology-in-india%E2%80%99s-real-retail-sector/
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    products and managing software projects and infrastructure for large financial institutions

    tell us that a standardized product with solution for all has not been developed yet. And a

    pure service based product where you get what you want has its own set of problems

    why re-invent the wheel that already exists. The answer is perhaps somewhere in between

    and it is too early for us to comment about the proportion in which the two should be. On

    an emotional basis, it is a pleasure to ask somebody to develop something for your

    business exactly what you want. You will also seed the local IT market. Would you

    rather buy a custom made bed or buy a standard and get adjusted to it.

    Considering the number of queries that we have got from various quarters like shop

    keepers (mainly), textile units small and medium scale and many others in areas

    relating to Accounting, Billing, Value Added Tax (VAT), Income tax, Inventory

    Management and many others; we came to a conclusion that the real Indian retail sector

    has to be investigated. In the meanwhile we though we will put across out experiences to

    our folks and other our peers in the industry who face similar questions.

    If one has already decided to get that contact of yours to write a new software please keep

    in mind a few things you may actually be spending your money on it. We have tried to

    list them here randomly.

    1. Purpose: Does it serve the purpose that you wish to solve. Just visualize things

    like how the solution will look after every thing is done, ask the person to tell you

    how it will look, whether you, your assistants, your grand father who will sit at the

    cash box and other be able to use it. Can you generate the reports that you want. Are

    you complicating your life further and will you have to hire somebody else to work

    the software while you sell your goods. You will be surprised how much of problem

    it will be for you if you do not know how to click and where to click. If you are not

    convinced then do not loose heart, get the correct solution. Ensure that your

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    requirements are met and at the end of the day you should be doing things better and

    faster and making more money.

    2. Competence: Software may not be rocket science but it is not childs play either.

    Does the person developing the application have the necessary competence. As it

    takes experience to run a shop like yours it takes a lot of experience to conceptualize

    and execute an IT project. This does not mean that you should drop your young

    friend from the project. The right way would be to assign a mentor, somebody who

    knows. There could be a few who would want to do consultancy for free out of good

    will.

    3. Organization: I am not speaking about the company here, the person who is

    developing the product should have the capability to provide solution in organized

    parts. It is like building a great institution, we need not do everything in one go, but

    in steps. The organization should be clear. In addition, the trend in technology and

    also needs change rapidly. The person developing the application should have the

    capability to envisage all these needs or atleast make provisions for them. You dont

    want to be stuck with something that is not changeable but your business will.

    4. Hardware and other software: Software require a computer to run, you know

    this. Your relative may be developing something that will require investment to

    work on. Clearly understand your costs for this. What you will require is not just a

    computer but many other software that will be required to run on it. These are

    typically Operating system like Windows and other things on which the software

    will run. These are not free. Taking the discussion further some of these will become

    old models so to say. Therefore, your friend should know what is happening in the

    market. He may use something cheap but tomorrow it may not be available in the

    market, this is more like your spare parts. Your may not get them. As much as

    possible get something that is well known.

    5. Running Costs: Like your car will require petrol, diesel or otherfuel your

    computer and your new software has running costs. One the one hand there are

    standards issues but you should also keep in mind that your software also require

    repairs and you will require a mechanic for it. This could involve costs.

    6. Maintenance: Extending the previous point, once you have installed the software

    your friend will have to be the mechanic. He should not run away or get into some

    other job. This you should take care.

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    7. Electricity: In India, electricity is still an issue. What will you do when there is

    no current. Think about it, will you write it in a book and then input it into the

    computer. Your friend should answer that question.

    8. Backup: Your computer may crash (it does believe me) and what will happen to

    your data. Your software should make provision for back up and more importantly

    recovery. The data backed up and recovered should not be out of sync. This is a big

    subject.

    9. Regulations: This relates to government, currently this may not be a big deal in a

    software, but it will be in the future.

    10. Other applications: You may want to data that is created by your

    software to be fed into other software like tally. This should be possible. Design your

    requirements appropriately.

    11. Language: This is another point that you should consider. For the moment

    let us leave it to English. Do you have a key board in your local language.

    12. Security: Have a basic security atleast. It is ultimately your data and you

    should not let somebody tamper with it. More the security, the better it is.

    13. User Manuals: If you have a problem or you dont know how to use it

    you will need something to refer to. Get the user manuals preferably in your

    language preferably.

    14. Data: This is something more into the software. If you can get a data

    model.

    Competition is increasing at all levels. Biggies are entering small business in the

    name of consumption power of the masses. They are well armed. IT is sufficiently

    powerful ammunition for smaller players to compete with the big fishes. Perhaps, this

    trend will herald a new era of software product and services in India where IT is not

    exclusive but instead is a common commodity used by all and sundry whether

    custom made or productized.

    .

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    Factors of new technology adoption in the retail sector.

    In recent years, small manufacturing enterprises have been implementing new

    computerized technologies at an every-increasing rate (Acs & Audretsch, 1990; Julien,

    Estime, & Drilhon, 1993), and the trend is being accelerated by international competition,

    in particular by the opening up of national boundaries. However, the same urgency does

    not seem to exist in the commercial and service sectors, especially among independent

    retailers (Robertson & Gatignon, 1986; Treadgold, 1989; Julien & Thibodeau, 1991).

    Certainly, competitive pressure is relatively less intense in these sectors, or at the very

    least, certain small businesses have an advantage in terms of location, knowledge of their

    clients and their merchandise, or profit from niches created by market segmentation (for

    example, gourmet food stores or high fashion boutiques), They are thus under less

    pressure to become computerized; they may also be less likely to do so and may not

    believe new information technologies to be very useful because, for example in

    merchandise analysis, they know their customers and merchandise intimately.

    Many small retailers, though, whose ability to differentiate themselves from their

    competitors is limited, are feeling increasing competitive pressures, especially with thegrowth of chains and the advent of warehouse stores. A majority of these have neither the

    experience nor the financial resources required to plan, implement, and operate a

    computer-based information system (Raymond & Lorrain, 1992). But others have begun

    to systematically install new point-of-sales (POS) terminals or link up to wholesalers by

    tele-computing or electronic data interchange (EDI) (Sweeney, Putnam, Brooks, Hyde,

    Lee, Rubel, Rossiter, Armstrong, & Koenigsberg, 1990; Blili & Raymond, 1993).

    There may be many reasons for these behavioral differences, even among firms in the

    same industry facing the same type of market. In the manufacturing sector, macro-

    economic factors such as the rate of economic growth and the competitive structure of the

    industry can be determinant (Bouchut, Cochet, & Jacot, 1984; Julien & Thibodeau,

    1991). Researchers have also shown that more "technology-consuming" firms are

    distinguished from others by: greater profitability, the differential cost of new equipment

    (Mansfield, 1971, 1975; Khan & Manopichetwattana, 1989); the management profile or

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    the owner-manager's personal characteristics (Miller & Toulouse, 1986); organizational

    complexity, centralization and formalization (Cohn & Turyn, 1980, 1984; Meyer & Goes,

    1987; Collins, Hage, & Hull, 1988); strategy type (Garsombke & Garsombke, 1989); and

    the quality of technological information obtained together with the capacity to process it

    (Blili & Raymond, 1993; Julien, Carriere, & Hebert, 1988; Gatignon & Robertson, 1989).

    However, very little research has been done on the reasons for new technology adoption

    in the service and retail sectors. To our knowledge, only Treadgold (1989) and Hogarth-

    Scott and Parkinson (1990) have examined the question. Treadgold showed that

    differences in new technology adoption could be explained by the type of external

    organization (for example, between independent businesses and businesses belonging to

    groups) and the industry sector. Hogarth-Scott and Parkinson, for their part, showed that

    the limited use of EDI technologies among independent businesses stemmed from theirfear of losing their independence. Miller, Glick, Yau-De, & Huber, (1991) have also

    indicated that organizations in the retail and service sectors have narrower ranges than in

    manufacturing on both technology and structure variables, and thus tend to exhibit

    weaker technology-structure relationships

    The aim of this research, using empirical evidence, was to identify organizational,

    structural, and strategic factors underlying the level of penetration of various

    management, service, and information technologies among small retailers, including both

    independent businesses and those affiliated to trade banners or buying combines.

    Potential factors were identified from the previously cited literature, and in particular

    from Julien, Carriere, and Hebert's (1988) study done in the manufacturing sector.

    RESEARCH MODEL

    The research model is presented in Figure 1. A first set of factors, thought to influence

    new technology adoption in small retail firms, describes the structural sophistication of

    the firm in terms of centralization and complexity. In the organization theory literature,

    structure has often been characterized along these two dimensions or composite factors

    (Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-

    structure relationship (Miller et al., 1991). Decentralizing and complexifying structure

    implies more elaborate communication, coordination, and control The aim of this

    research, using empirical evidence, was to identify organizational, structural, and

    strategic factors underlying the level of penetration of various management, service, and

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    information technologies among small retailers, including both independent businesses

    and those affiliated to trade banners or buying combines. Potential factors were identified

    from the previously cited literature, and in particular from Julien, Carriere, and Hebert's

    (1988) study done in the manufacturing sector.

    RESEARCH MODEL

    The research model is presented in Figure 1. A first set of factors, thought to influence

    new technology adoption in small retail firms, describes the structural sophistication of

    the firm in terms of centralization and complexity. In the organization theory literature,

    structure has often been characterized along these two dimensions or composite factors

    (Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-

    structure relationship (Miller et al., 1991). Decentralizing and complexifying structure

    implies more elaborate communication, coordination, and control Cohn & Turyn, 1984;

    Miller & Toulouse, 1986; Raymond, Pare, & Bergeron, 1993).

    The second set of adoption factors is strategic in nature, identifying the level of

    assertiveness, rationality, and interaction in business decision processes. These three

    factors have emerged in the strategy literature as fundamental dimensions or derivative

    constructs of the strategy concept (Miller, 1987; Venkatraman, 1989). The first

    dimension refers to the proactiveness of decisions and risk taking. The second one

    concerns the planning and formulation of strategies. The third one refers to the

    political/bargaining processes that bear upon decisions. Information technology has

    become one of the key elements in the definition and realization of strategic objectives

    (Vitale, Ives, & Beath, 1986). In an increasingly complex environment, organizations

    must "align" their use of information technology with the implementation of their

    strategic decisions (Chan & Huff, 1993). Thus, when they are more proactive, more

    future/planning-oriented, and when more executives interact in strategy making, retailers

    would be more apt to implement computer-based information systems resulting from or

    in support of their strategy (Shrivastava & Grant, 1985; Schroeder, Gopinath, &

    Congden, 1989).

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    The third set of factors thought to influence new technology adoption in small retail firms

    are organizational, including size, sector, and status (independent or affiliated).

    Organization theorists have found the first two contingency variables to consistently play

    an important role in structure-technology-strategy relationships (Ford & Slocum, 1977;

    Miller et al., 1991). One expects larger firms to have adopted more sophisticated

    technologies (Dewar & Dutton, 1986; Raymond, Pare, & Bergeron, 1993). The same can

    be said of firms in more information-intensive retail sectors, e.g. hardware as opposed to

    clothing (Kimberly & Evanisko, 1981). Firms who become linked to banners or buying

    combines, as opposed to remaining independent, would also be greater users of

    information technology (Tornatsky & Klein, 1982). The greater technological

    sophistication obtained by retailers who cooperate among themselves would tend to

    reduce environmental uncertainty in terms of markets and competitors (Huber, 1984).

    The seven factors of new technology adoption were chosen due to their fundamental

    nature as descriptors of structure, strategy, and organizational contingencies. These

    factors have also been identified as fundamental determinants of technology, both

    theoretically and empirically, and all have been used previously in the small business

    research context. Note that many of the organization theory and strategic management

    studies cited here point to the interdependence of strategy and structure, and to the

    contingent role of size and sector in this regard. However, given the focus and objectives

    of this study, expected interrelationships between structure, strategy, and organizationalcontingencies were not made explicit in the research model.

    No distinction was made between management and production technologies as indicators

    of technological levels because in retailing, unlike manufacturing (Raymond & Pare,

    1992), it is difficult to differentiate the two. In addition, the actual level of independence

    or involvement in a group was not measured, even though some retailing groups (buying

    combines, trade banners, coops, franchises) exercise more control over their members

    than others. However, franchisees were excluded from the study because, in contrast to

    the other groups, their independence is very restricted (Castrogiovanni, Bennett, &

    Combs, 1993). In the Canadian province of Quebec, where the survey took place,

    independent retailers and members of buying groups or coops are responsible for more

    than 72% of all retail sales, at the expense of chains and megastores, whereas in the rest

    of Canada and in the U.S.A., their share is much smaller

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    RESEARCH METHODOLOGY

    The survey was carried out by collecting data from a sample of small retailers in the food,

    hardware, and ladies' garment sectors. Their names were obtained from the central

    business data bank of Quebec's commission on health and safety in the workplace(CSST). The survey was performed in two stages. First, 1,200 letters were sent out to the

    addresses provided by the CSST, requesting an interview with the owner (4.8% of these

    were returned due to improper addresses or out-of-business situations). Among the 232

    (19.3%) who were willing to cooperate, a total of 79 retailers were selected for semi-

    structured interviews in the field, with the help of a questionnaire. Using CSST data for

    the entire 1,200-firm population, the 79 firms were chosen on a stratified sampling basis,

    to be statistically representative of this population in terms of size and regional

    distribution for each sector. This was verified through chi-square and t tests. Thequestionnaire included 56 closed questions and six open questions, divided into four

    sections: the firm's demographics (size, status, etc.), structure, computer hardware and

    software, and strategy. A pre-test was done using three firms from each of the three

    sectors. Interviewing was deemed preferable to mailing the questionnaire, due to the

    technical or open nature of many questions, and to acquire more in-depth information

    Two main types of technology were distinguished in the survey: hardware for business

    computing (computers), point-of-sales computing (computerized cash registers, whether

    or not linked to a central processing unit), and tele-computing (electronic links with

    outside firms, usually wholesalers); and software, assessed by the nature of the

    applications portfolio. The measures of hardware and software technology adoption, i.e.

    the dependent variables, were adapted from previously developed instruments by Julien,

    Hebert, and Carriere (1988) and by Raymond and Lorrain (1992). Two main dimensions

    of structure--centralization and complexity--were assessed by measuring the managerial

    hierarchy (number of managers excluding the owners(s)/all personnel) and the

    administrative apparatus (clerical workers/all personnel), both measures previously

    validated and used in a small business context (Paulson & Stump, 1979). Complexity was

    also ascertained by the presence of a management committee (Julien, Hebert & Carriere,

    1988). The same was done with the three principal components of strategy, namely

    assertiveness, rationality and interaction. Miller's (1987) instrument was used to measure

    strategic orientation (or proactiveness: reactive-proactive) for the first dimension,

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    organizational time-frame (or futurity: short-long term) for the second one, and strategic

    decision making (individual-consensual) for the third one.

    Table 1 shows the descriptive statistics of the research variables. Thirty-six percent of

    firms operated in the food sector (grocery stores, butchers, etc.), 40% in the hardwaresector and 24% in the garment sector. They employed an average of 14.5 people

    (excluding owners), including 2.5 office staff. In all, slightly over 50% of the businesses

    were affiliated to a trade banner or buying combine, and 46% had a management

    committee. Strategically speaking, they were fairly proactive (4.0 on a scale of 1 to 7),

    had a medium time-frame (2.7 on a scale of 1 to 5), and shared the decision-making

    process to a moderate degree (4.0 on a scale of 1 to 7).

    ADOPTION OF NEW TECHNOLOGIES

    The overall survey results show that 63 of the 79 firms questioned (79.7%) used at least

    one computer-based technology (i.e. electronic cash registers), a higher number

    TABULAR DATA OMITTED than the 71% forecasted by Collard (1989) for 1993 in the

    United States. The percentage is higher in the food sector (92.8%) than in the hardware

    (84.4%) and garment (57.9%) sectors. In all, 36 firms (46.2%) used only stand-alone

    electronic cash registers, 11 (14.0%) used cash registers linked to a central register, and

    16 (20.5%) had a cash register system linked to a computer. Eight firms (10.0%) had only

    a fax or telex, 31 (39.4%) maintained outside links by modem for batch data transfers or

    financial transactions (with banks), and 21 (26.9%) maintained systematic outside links

    through computers or terminals (EDI).

    The number of business computing applications varied from zero to four. Eight firms

    (10.1%) indicated using four applications, 16 (20.2%) used three, ten (12.7%) used two,

    and four (5.1%) used only one application. In all, 41 firms (51.9%) did not use any form

    of business computing. Overall, the type of technology least used by sample firms turned

    out to be business computing and related applications. The other two technologies were

    more widespread, as only 15 firms (19.0%) did not have an electronic cash register (POS

    computing) and 18 (22.8%) did not have an electronic link with an outside organization

    (tele-computing). Table 2 summarizes mean adoption rates for each technology (using 5-

    point sophistication scales)

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    DETERMINANT FACTORS OF NEW TECHNOLOGY ADOPTION

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    In recent years, small manufacturing enterprises have been implementing new

    computerized technologies at an every-increasing rate (Acs & Audretsch, 1990; Julien,

    Estime, & Drilhon, 1993), and the trend is being accelerated by international competition,

    in particular by the opening up of national boundaries. However, the same urgency does

    not seem to exist in the commercial and service sectors, especially among independent

    retailers (Robertson & Gatignon, 1986; Treadgold, 1989; Julien & Thibodeau, 1991).

    Certainly, competitive pressure is relatively less intense in these sectors, or at the very

    least, certain small businesses have an advantage in terms of location, knowledge of their

    clients and their merchandise, or profit from niches created by market segmentation (for

    example, gourmet food stores or high fashion boutiques), They are thus under less

    pressure to become computerized; they may also be less likely to do so and may not

    believe new information technologies to be very useful because, for example inmerchandise analysis, they know their customers and merchandise intimately.

    Many small retailers, though, whose ability to differentiate themselves from their

    competitors is limited, are feeling increasing competitive pressures, especially with the

    growth of chains and the advent of warehouse stores. A majority of these have neither the

    experience nor the financial resources required to plan, implement, and operate a

    computer-based information system (Raymond & Lorrain, 1992). But others have begun

    to systematically install new point-of-sales (POS) terminals or link up to wholesalers by

    tele-computing or electronic data interchange (EDI) (Sweeney, Putnam, Brooks, Hyde,

    Lee, Rubel, Rossiter, Armstrong, & Koenigsberg, 1990; Blili & Raymond, 1993).

    There may be many reasons for these behavioral differences, even among firms in the

    same industry facing the same type of market. In the manufacturing sector, macro-

    economic factors such as the rate of economic growth and the competitive structure of the

    http://www.allbusiness.com/government/government-bodies-offices-us-federal-government/11755722-1.htmlhttp://www.allbusiness.com/company-activities-management/company-structures-ownership/11803672-1.htmlhttp://www.allbusiness.com/company-activities-management/product-management/14814364-1.htmlhttp://www.allbusiness.com/government/government-bodies-offices-us-federal-government/11755722-1.htmlhttp://www.allbusiness.com/company-activities-management/company-structures-ownership/11803672-1.htmlhttp://www.allbusiness.com/company-activities-management/product-management/14814364-1.html
  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    industry can be determinant (Bouchut, Cochet, & Jacot, 1984; Julien & Thibodeau,

    1991). Researchers have also shown that more "technology-consuming" firms are

    distinguished from others by: greater profitability, the differential cost of new equipment

    (Mansfield, 1971, 1975; Khan & Manopichetwattana, 1989); the management profile or

    the owner-manager's personal characteristics (Miller & Toulouse, 1986); organizational

    complexity, centralization and formalization (Cohn & Turyn, 1980, 1984; Meyer & Goes,

    1987; Collins, Hage, & Hull, 1988); strategy type (Garsombke & Garsombke, 1989); and

    the quality of technological information obtained together with the capacity to process it

    (Blili & Raymond, 1993; Julien, Carriere, & Hebert, 1988; Gatignon & Robertson, 1989).

    However, very little research has been done on the reasons for new technology adoption

    in the service and retail sectors. To our knowledge, only Treadgold (1989) and Hogarth-

    Scott and Parkinson (1990) have examined the question. Treadgold showed thatdifferences in new technology adoption could be explained by the type of external

    organization (for example, between independent businesses and businesses belonging to

    groups) and the industry sector. Hogarth-Scott and Parkinson, for their part, showed that

    the limited use of EDI technologies among independent businesses stemmed from their

    fear of losing their independence. Miller, Glick, Yau-De, & Huber, (1991) have also

    indicated that organizations in the retail and service sectors have narrower ranges than in

    manufacturing on both technology and structure variables, and thus tend to exhibit

    weaker technology-structure relationships.

    The aim of this research, using empirical evidence, was to identify organizational,

    structural, and strategic factors underlying the level of penetration of various

    management, service, and information technologies among small retailers, including both

    independent businesses and those affiliated to trade banners or buying combines.

    Potential factors were identified from the previously cited literature, and in particular

    from Julien, Carriere, and Hebert's (1988) study done in the manufacturing sector.

    RESEARCH MODEL

    The research model is presented in Figure 1. A first set of factors, thought to influence

    new technology adoption in small retail firms, describes the structural sophistication of

    the firm in terms of centralization and complexity. In the organization theory literature,

    structure has often been characterized along these two dimensions or composite factors

    (Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-

  • 8/6/2019 RFID Technology in the Indian Retail Sector

    13/42

    structure relationship (Miller et al., 1991). Decentralizing and complexifying structure

    implies more elaborate communication, coordination, and control mechanisms; this in

    turn requires an infrastructure that can be better enabled through information technology

    (Huber, 1984; Leifer, 1988). Hence, more decentralized management and complex

    administrative structures should lead to greater adoption of information technologies by

    retailers (Cohn & Turyn, 1984; Miller & Toulouse, 1986; Raymond, Pare, & Bergeron,

    1993).

    The second set of adoption factors is strategic in nature, identifying the level of

    assertiveness, rationality, and interaction in business decision processes. These three

    factors have emerged in the strategy literature as fundamental dimensions or derivative

    constructs of the strategy concept (Miller, 1987; Venkatraman, 1989). The first

    dimension refers to the proactiveness of decisions and risk taking. The second oneconcerns the planning and formulation of strategies. The third one refers to the

    political/bargaining processes that bear upon decisions. Information technology has

    become one of the key elements in the definition and realization of strategic objectives

    (Vitale, Ives, & Beath, 1986). In an increasingly complex environment, organizations

    must "align" their use of information technology with the implementation of their

    strategic decisions (Chan & Huff, 1993). Thus, when they are more proactive, more

    future/planning-oriented, and when more executives interact in strategy making, retailers

    would be more apt to implement computer-based information systems resulting from orin support of their strategy (Shrivastava & Grant, 1985; Schroeder, Gopinath, &

    Congden, 1989).

    The third set of factors thought to influence new technology adoption in small retail firms

    are organizational, including size, sector, and status (independent or affiliated).

    Organization theorists have found the first two contingency variables to consistently play

    an important role in structure-technology-strategy relationships (Ford & Slocum, 1977;

    Miller et al., 1991). One expects larger firms to have adopted more sophisticated

    technologies (Dewar & Dutton, 1986; Raymond, Pare, & Bergeron, 1993). The same can

    be said of firms in more information-intensive retail sectors, e.g. hardware as opposed to

    clothing (Kimberly & Evanisko, 1981). Firms who become linked to banners or buying

    combines, as opposed to remaining independent, would also be greater users of

    information technology (Tornatsky & Klein, 1982). The greater technological

  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    sophistication obtained by retailers who cooperate among themselves would tend to

    reduce environmental uncertainty in terms of markets and competitors (Huber, 1984).

    The seven factors of new technology adoption were chosen due to their fundamental

    nature as descriptors of structure, strategy, and organizational contingencies. Thesefactors have also been identified as fundamental determinants of technology, both

    theoretically and empirically, and all have been used previously in the small business

    research context. Note that many of the organization theory and strategic management

    studies cited here point to the interdependence of strategy and structure, and to the

    contingent role of size and sector in this regard. However, given the focus and objectives

    of this study, expected interrelationships between structure, strategy, and organizational

    contingencies were not made explicit in the research model.

    No distinction was made between management and production technologies as indicators

    of technological levels because in retailing, unlike manufacturing (Raymond & Pare,

    1992), it is difficult to differentiate the two. In addition, the actual level of independence

    or involvement in a group was not measured, even though some retailing groups (buying

    combines, trade banners, coops, franchises) exercise more control over their members

    than others. However, franchisees were excluded from the study because, in contrast to

    the other groups, their independence is very restricted (Castrogiovanni, Bennett, &

    Combs, 1993). In the Canadian province of Quebec, where the survey took place,

    independent retailers and members of buying groups or coops are responsible for more

    than 72% of all retail sales, at the expense of chains and megastores, whereas in the rest

    of Canada and in the U.S.A., their share is much smaller.

    RESEARCH METHODOLOGY

    The survey was carried out by collecting data from a sample of small retailers in the food,

    hardware, and ladies' garment sectors. Their names were obtained from the central

    business data bank of Quebec's commission on health and safety in the workplace

    (CSST). The survey was performed in two stages. First, 1,200 letters were sent out to the

    addresses provided by the CSST, requesting an interview with the owner (4.8% of these

    were returned due to improper addresses or out-of-business situations). Among the 232

    (19.3%) who were willing to cooperate, a total of 79 retailers were selected for semi-

    structured interviews in the field, with the help of a questionnaire. Using CSST data for

    the entire 1,200-firm population, the 79 firms were chosen on a stratified sampling basis,

  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    to be statistically representative of this population in terms of size and regional

    distribution for each sector. This was verified through chi-square and t tests. The

    questionnaire included 56 closed questions and six open questions, divided into four

    sections: the firm's demographics (size, status, etc.), structure, computer hardware and

    software, and strategy. A pre-test was done using three firms from each of the three

    sectors. Interviewing was deemed preferable to mailing the questionnaire, due to the

    technical or open nature of many questions, and to acquire more in-depth information.

    Two main types of technology were distinguished in the survey: hardware for business

    computing (computers), point-of-sales computing (computerized cash registers, whether

    or not linked to a central processing unit), and tele-computing (electronic links with

    outside firms, usually wholesalers); and software, assessed by the nature of the

    applications portfolio. The measures of hardware and software technology adoption, i.e.the dependent variables, were adapted from previously developed instruments by Julien,

    Hebert, and Carriere (1988) and by Raymond and Lorrain (1992). Two main dimensions

    of structure--centralization and complexity--were assessed by measuring the managerial

    hierarchy (number of managers excluding the owners(s)/all personnel) and the

    administrative apparatus (clerical workers/all personnel), both measures previously

    validated and used in a small business context (Paulson & Stump, 1979). Complexity was

    also ascertained by the presence of a management committee (Julien, Hebert & Carriere,

    1988). The same was done with the three principal components of strategy, namelyassertiveness, rationality and interaction. Miller's (1987) instrument was used to measure

    strategic orientation (or proactiveness: reactive-proactive) for the first dimension,

    organizational time-frame (or futurity: short-long term) for the second one, and strategic

    decision making (individual-consensual) for the third one.

    Table 1 shows the descriptive statistics of the research variables. Thirty-six percent of

    firms operated in the food sector (grocery stores, butchers, etc.), 40% in the hardware

    sector and 24% in the garment sector. They employed an average of 14.5 people

    (excluding owners), including 2.5 office staff. In all, slightly over 50% of the businesses

    were affiliated to a trade banner or buying combine, and 46% had a management

    committee. Strategically speaking, they were fairly proactive (4.0 on a scale of 1 to 7),

    had a medium time-frame (2.7 on a scale of 1 to 5), and shared the decision-making

    process to a moderate degree (4.0 on a scale of 1 to 7).

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    ADOPTION OF NEW TECHNOLOGIES

    The overall survey results show that 63 of the 79 firms questioned (79.7%) used at least

    one computer-based technology (i.e. electronic cash registers), a higher number

    TABULAR DATA OMITTED than the 71% forecasted by Collard (1989) for 1993 in theUnited States. The percentage is higher in the food sector (92.8%) than in the hardware

    (84.4%) and garment (57.9%) sectors. In all, 36 firms (46.2%) used only stand-alone

    electronic cash registers, 11 (14.0%) used cash registers linked to a central register, and

    16 (20.5%) had a cash register system linked to a computer. Eight firms (10.0%) had only

    a fax or telex, 31 (39.4%) maintained outside links by modem for batch data transfers or

    financial transactions (with banks), and 21 (26.9%) maintained systematic outside links

    through computers or terminals (EDI).

    The number of business computing applications varied from zero to four. Eight firms

    (10.1%) indicated using four applications, 16 (20.2%) used three, ten (12.7%) used two,

    and four (5.1%) used only one application. In all, 41 firms (51.9%) did not use any form

    of business computing. Overall, the type of technology least used by sample firms turned

    out to be business computing and related applications. The other two technologies were

    more widespread, as only 15 firms (19.0%) did not have an electronic cash register (POS

    computing) and 18 (22.8%) did not have an electronic link with an outside organization

    (tele-computing). Table 2 summarizes mean adoption rates for each technology (using 5-

    point sophistication scales).

    DETERMINANT FACTORS OF NEW TECHNOLOGY ADOPTION

    Shown in Table 3 is the intercorrelation matrix of the independent variables. Given its

    highly significant relationship with five other factors, size was removed from further data

    analysis to reduce problems due to multicollinearity (Huang, 1970). The same was done

    with the decision-making variable, as it is strongly correlated with the other two strategy

    variables. Note that after removal of these two variables, two intercorrelations

    TABULAR DATA OMITTED greater than 0.3 remain, that is, firms in the clothing

    sector and firms with a larger bureaucracy (administrative apparatus) are less likely to

    have an affiliated status (r = -0.52, r = -0.35).

    As hypothesized, differences in levels of hardware and software technology adoption by

    retailers are due to a number of organizational, structural, and strategic factors.

  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    TABULAR DATA OMITTED

    Shown in Table 4 are the results of stepwise regression analyses on the four technology

    variables, revealing the determinant factors in each case. Retailers who adopt business

    computing are less likely to be in the food sector and tend to be affiliated to a buyingcombine or trade banner. They are more decentralized, i.e. show a higher ratio of

    managers (managerial hierarchy), and are more likely to have a management committee.

    Strategic factors do not seem to come into play here.

    The adoption of POS computing is determined by a different set of factors. Clothing

    merchants are less apt to employ this technology, as are firms with a larger ratio of

    clerical personnel (administrative apparatus). In addition, firms with POS technology

    have a longer organization time-frame. The use of tele-computing is mostly determined

    by the retailer's status as member of a combine or banner, as expected. Firms who have

    implemented EDI are also more future-oriented than others, confirming Blili and

    Raymond's (1993) conjecture.

    Not surprisingly, hardware stores, with their greater information needs (e.g. for inventory

    management), are the ones with the more extensive applications portfolio (software),

    while more decentralized firms implement a more sophisticated management information

    system. These results are in line with the technology-structure relationships found by

    Raymond, Pare, and Bergeron (1993). Also, more proactive and future-oriented retailfirms implement a more extensive applications portfolio. This confirms the mutually

    determining impact of strategy and information systems in the context of SMEs (Blili &

    Raymond, 1993).

    Table 4

    Regression Analyses on the Four Technology Variables

    Standardized betas(a)

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  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    In recent years, small manufacturing enterprises have been implementing new

    computerized technologies at an every-increasing rate (Acs & Audretsch, 1990; Julien,

    Estime, & Drilhon, 1993), and the trend is being accelerated by international competition,

    in particular by the opening up of national boundaries. However, the same urgency does

    not seem to exist in the commercial and service sectors, especially among independent

    retailers (Robertson & Gatignon, 1986; Treadgold, 1989; Julien & Thibodeau, 1991).

    Certainly, competitive pressure is relatively less intense in these sectors, or at the very

    least, certain small businesses have an advantage in terms of location, knowledge of their

    clients and their merchandise, or profit from niches created by market segmentation (for

    example, gourmet food stores or high fashion boutiques), They are thus under less

    pressure to become computerized; they may also be less likely to do so and may not

    believe new information technologies to be very useful because, for example in

    merchandise analysis, they know their customers and merchandise intimately.

    Many small retailers, though, whose ability to differentiate themselves from their

    competitors is limited, are feeling increasing competitive pressures, especially with the

    growth of chains and the advent of warehouse stores. A majority of these have neither the

    experience nor the financial resources required to plan, implement, and operate a

    computer-based information system (Raymond & Lorrain, 1992). But others have begun

    to systematically install new point-of-sales (POS) terminals or link up to wholesalers by

    tele-computing or electronic data interchange (EDI) (Sweeney, Putnam, Brooks, Hyde,

    Lee, Rubel, Rossiter, Armstrong, & Koenigsberg, 1990; Blili & Raymond, 1993).

    There may be many reasons for these behavioral differences, even among firms in the

    same industry facing the same type of market. In the manufacturing sector, macro-

    economic factors such as the rate of economic growth and the competitive structure of the

    industry can be determinant (Bouchut, Cochet, & Jacot, 1984; Julien & Thibodeau,

    1991). Researchers have also shown that more "technology-consuming" firms are

    distinguished from others by: greater profitability, the differential cost of new equipment

    (Mansfield, 1971, 1975; Khan & Manopichetwattana, 1989); the management profile or

    the owner-manager's personal characteristics (Miller & Toulouse, 1986); organizational

    complexity, centralization and formalization (Cohn & Turyn, 1980, 1984; Meyer & Goes,

  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    1987; Collins, Hage, & Hull, 1988); strategy type (Garsombke & Garsombke, 1989); and

    the quality of technological information obtained together with the capacity to process it

    (Blili & Raymond, 1993; Julien, Carriere, & Hebert, 1988; Gatignon & Robertson, 1989).

    However, very little research has been done on the reasons for new technology adoption

    in the service and retail sectors. To our knowledge, only Treadgold (1989) and Hogarth-

    Scott and Parkinson (1990) have examined the question. Treadgold showed that

    differences in new technology adoption could be explained by the type of external

    organization (for example, between independent businesses and businesses belonging to

    groups) and the industry sector. Hogarth-Scott and Parkinson, for their part, showed that

    the limited use of EDI technologies among independent businesses stemmed from their

    fear of losing their independence. Miller, Glick, Yau-De, & Huber, (1991) have also

    indicated that organizations in the retail and service sectors have narrower ranges than in

    manufacturing on both technology and structure variables, and thus tend to exhibit

    weaker technology-structure relationships.

    The aim of this research, using empirical evidence, was to identify organizational,

    structural, and strategic factors underlying the level of penetration of various

    management, service, and information technologies among small retailers, including both

    independent businesses and those affiliated to trade banners or buying combines.

    Potential factors were identified from the previously cited literature, and in particular

    from Julien, Carriere, and Hebert's (1988) study done in the manufacturing sector.

    RESEARCH MODEL

    The research model is presented in Figure 1. A first set of factors, thought to influence

    new technology adoption in small retail firms, describes the structural sophistication of

    the firm in terms of centralization and complexity. In the organization theory literature,

    structure has often been characterized along these two dimensions or composite factors

    (Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-

  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    structure relationship (Miller et al., 1991). Decentralizing and complexifying structure

    implies more elaborate communication, coordination, and control mechanisms; this in

    turn requires an infrastructure that can be better enabled through information technology

    (Huber, 1984; Leifer, 1988). Hence, more decentralized management and complex

    administrative structures should lead to greater adoption of information technologies by

    retailers (Cohn & Turyn, 1984; Miller & Toulouse, 1986; Raymond, Pare, & Bergeron,

    1993).

    The second set of adoption factors is strategic in nature, identifying the level of

    assertiveness, rationality, and interaction in business decision processes. These three

    factors have emerged in the strategy literature as fundamental dimensions or derivative

    constructs of the strategy concept (Miller, 1987; Venkatraman, 1989). The first

    dimension refers to the proactiveness of decisions and risk taking. The second one

    concerns the planning and formulation of strategies. The third one refers to the

    political/bargaining processes that bear upon decisions. Information technology has

    become one of the key elements in the definition and realization of strategic objectives

    (Vitale, Ives, & Beath, 1986). In an increasingly complex environment, organizations

    must "align" their use of information technology with the implementation of their

    strategic decisions (Chan & Huff, 1993). Thus, when they are more proactive, more

    future/planning-oriented, and when more executives interact in strategy making, retailers

    would be more apt to implement computer-based information systems resulting from or

    in support of their strategy (Shrivastava & Grant, 1985; Schroeder, Gopinath, &

    Congden, 1989).

    The third set of factors thought to influence new technology adoption in small retail firms

    are organizational, including size, sector, and status (independent or affiliated).

    Organization theorists have found the first two contingency variables to consistently play

    an important role in structure-technology-strategy relationships (Ford & Slocum, 1977;

    Miller et al., 1991). One expects larger firms to have adopted more sophisticated

    technologies (Dewar & Dutton, 1986; Raymond, Pare, & Bergeron, 1993). The same can

    be said of firms in more information-intensive retail sectors, e.g. hardware as opposed to

    clothing (Kimberly & Evanisko, 1981). Firms who become linked to banners or buying

  • 8/6/2019 RFID Technology in the Indian Retail Sector

    21/42

    combines, as opposed to remaining independent, would also be greater users of

    information technology (Tornatsky & Klein, 1982). The greater technological

    sophistication obtained by retailers who cooperate among themselves would tend to

    reduce environmental uncertainty in terms of markets and competitors (Huber, 1984).

    The seven factors of new technology adoption were chosen due to their fundamental

    nature as descriptors of structure, strategy, and organizational contingencies. These

    factors have also been identified as fundamental determinants of technology, both

    theoretically and empirically, and all have been used previously in the small business

    research context. Note that many of the organization theory and strategic management

    studies cited here point to the interdependence of strategy and structure, and to the

    contingent role of size and sector in this regard. However, given the focus and objectives

    of this study, expected interrelationships between structure, strategy, and organizational

    contingencies were not made explicit in the research model.

    No distinction was made between management and production technologies as indicators

    of technological levels because in retailing, unlike manufacturing (Raymond & Pare,

    1992), it is difficult to differentiate the two. In addition, the actual level of independence

    or involvement in a group was not measured, even though some retailing groups (buying

    combines, trade banners, coops, franchises) exercise more control over their members

    than others. However, franchisees were excluded from the study because, in contrast to

    the other groups, their independence is very restricted (Castrogiovanni, Bennett, &

    Combs, 1993). In the Canadian province of Quebec, where the survey took place,

    independent retailers and members of buying groups or coops are responsible for more

    than 72% of all retail sales, at the expense of chains and megastores, whereas in the rest

    of Canada and in the U.S.A., their share is much smaller.

    RESEARCH METHODOLOGY

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    The survey was carried out by collecting data from a sample of small retailers in the food,

    hardware, and ladies' garment sectors. Their names were obtained from the central

    business data bank of Quebec's commission on health and safety in the workplace

    (CSST). The survey was performed in two stages. First, 1,200 letters were sent out to the

    addresses provided by the CSST, requesting an interview with the owner (4.8% of these

    were returned due to improper addresses or out-of-business situations). Among the 232

    (19.3%) who were willing to cooperate, a total of 79 retailers were selected for semi-

    structured interviews in the field, with the help of a questionnaire. Using CSST data for

    the entire 1,200-firm population, the 79 firms were chosen on a stratified sampling basis,

    to be statistically representative of this population in terms of size and regional

    distribution for each sector. This was verified through chi-square and t tests. The

    questionnaire included 56 closed questions and six open questions, divided into four

    sections: the firm's demographics (size, status, etc.), structure, computer hardware and

    software, and strategy. A pre-test was done using three firms from each of the three

    sectors. Interviewing was deemed preferable to mailing the questionnaire, due to the

    technical or open nature of many questions, and to acquire more in-depth information.

    Two main types of technology were distinguished in the survey: hardware for business

    computing (computers), point-of-sales computing (computerized cash registers, whether

    or not linked to a central processing unit), and tele-computing (electronic links with

    outside firms, usually wholesalers); and software, assessed by the nature of the

    applications portfolio. The measures of hardware and software technology adoption, i.e.

    the dependent variables, were adapted from previously developed instruments by Julien,

    Hebert, and Carriere (1988) and by Raymond and Lorrain (1992). Two main dimensions

    of structure--centralization and complexity--were assessed by measuring the managerial

    hierarchy (number of managers excluding the owners(s)/all personnel) and the

    administrative apparatus (clerical workers/all personnel), both measures previously

    validated and used in a small business context (Paulson & Stump, 1979). Complexity was

    also ascertained by the presence of a management committee (Julien, Hebert & Carriere,

    1988). The same was done with the three principal components of strategy, namely

    assertiveness, rationality and interaction. Miller's (1987) instrument was used to measure

    strategic orientation (or proactiveness: reactive-proactive) for the first dimension,

  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    organizational time-frame (or futurity: short-long term) for the second one, and strategic

    decision making (individual-consensual) for the third one.

    Table 1 shows the descriptive statistics of the research variables. Thirty-six percent of

    firms operated in the food sector (grocery stores, butchers, etc.), 40% in the hardware

    sector and 24% in the garment sector. They employed an average of 14.5 people

    (excluding owners), including 2.5 office staff. In all, slightly over 50% of the businesses

    were affiliated to a trade banner or buying combine, and 46% had a management

    committee. Strategically speaking, they were fairly proactive (4.0 on a scale of 1 to 7),

    had a medium time-frame (2.7 on a scale of 1 to 5), and shared the decision-making

    process to a moderate degree (4.0 on a scale of 1 to 7).

    ADOPTION OF NEW TECHNOLOGIES

    The overall survey results show that 63 of the 79 firms questioned (79.7%) used at least

    one computer-based technology (i.e. electronic cash registers), a higher number

    TABULAR DATA OMITTED than the 71% forecasted by Collard (1989) for 1993 in the

    United States. The percentage is higher in the food sector (92.8%) than in the hardware(84.4%) and garment (57.9%) sectors. In all, 36 firms (46.2%) used only stand-alone

    electronic cash registers, 11 (14.0%) used cash registers linked to a central register, and

    16 (20.5%) had a cash register system linked to a computer. Eight firms (10.0%) had only

    a fax or telex, 31 (39.4%) maintained outside links by modem for batch data transfers or

    financial transactions (with banks), and 21 (26.9%) maintained systematic outside links

    through computers or terminals (EDI).

    The number of business computing applications varied from zero to four. Eight firms

    (10.1%) indicated using four applications, 16 (20.2%) used three, ten (12.7%) used two,

    and four (5.1%) used only one application. In all, 41 firms (51.9%) did not use any form

    of business computing. Overall, the type of technology least used by sample firms turned

    out to be business computing and related applications. The other two technologies were

  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    more widespread, as only 15 firms (19.0%) did not have an electronic cash register (POS

    computing) and 18 (22.8%) did not have an electronic link with an outside organization

    (tele-computing). Table 2 summarizes mean adoption rates for each technology (using 5-

    point sophistication scales).

    DETERMINANT FACTORS OF NEW TECHNOLOGY ADOPTION

    Shown in Table 3 is the intercorrelation matrix of the independent variables. Given its

    highly significant relationship with five other factors, size was removed from further data

    analysis to reduce problems due to multicollinearity (Huang, 1970). The same was done

    with the decision-making variable, as it is strongly correlated with the other two strategy

    variables. Note that after removal of these two variables, two intercorrelations

    TABULAR DATA OMITTED greater than 0.3 remain, that is, firms in the clothing

    sector and firms with a larger bureaucracy (administrative apparatus) are less likely to

    have an affiliated status (r = -0.52, r = -0.35).

    As hypothesized, differences in levels of hardware and software technology adoption by

    retailers are due to a number of organizational, structural, and strategic factors.

    TABULAR DATA OMITTED

    Shown in Table 4 are the results of stepwise regression analyses on the four technology

    variables, revealing the determinant factors in each case. Retailers who adopt business

    computing are less likely to be in the food sector and tend to be affiliated to a buying

    combine or trade banner. They are more decentralized, i.e. show a higher ratio of

    managers (managerial hierarchy), and are more likely to have a management committee.

    Strategic factors do not seem to come into play here.

  • 8/6/2019 RFID Technology in the Indian Retail Sector

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    The adoption of POS computing is determined by a different set of factors. Clothing

    merchants are less apt to employ this technology, as are firms with a larger ratio of

    clerical personnel (administrative apparatus). In addition, firms with POS technology

    have a longer organization time-frame. The use of tele-computing is mostly determined

    by the retailer's status as member of a combine or banner, as expected. Firms who have

    implemented EDI are also more future-oriented than others, confirming Blili and

    Raymond's (1993) conjecture.

    Not surprisingly, hardware stores, with their greater information needs (e.g. for inventory

    management), are the ones with the more extensive applications portfolio (software),

    while more decentralized firms implement a more sophisticated management information

    system. These results are in line with the technology-structure relationships found by

    Raymond, Pare, and Bergeron (1993). Also, more proactive and future-oriented retail

    firms implement a more extensive applications portfolio. This confirms the mutually

    determining impact of strategy and information systems in the context of SMEs (Blili &

    Raymond, 1993).

    Table 4

    Regression Analyses on the Four Technology Variables

    Standardized betas(a)

    HARDWARE SOFTWARE

    ENTERPRISE TYPOLOGY AND NEW TECHNOLOGY ADOPTION

    To typify the sampled firms in terms of overall technology adoption, a hierarchical

    cluster analysis on the four technology (dependent) variables was used to divide the

    sampled firms into three groups: 45 firms using very few or no hardware and software

    technologies (type 1: LOW TECHNOLOGY); 18 favoring technology for administrative

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    and managerial purposes (type 2: MANAGEMENT TECHNOLOGY); and 16 using

    technologies to enhance organizational value and performance (type 3: VALUE

    TECHNOLOGY). Business computing is used equally by the firms in types 2 and 3;

    these two groups also exhibit the same level of sophistication in their applications

    portfolio. However, POS and tele-computing are used significantly more by type 3 than

    type 2 retailers. Type 1 firms use some POS and tele-computing but almost no business

    computing or applications.

    Table 5 presents a breakdown of the adoption factors (independent variables) for the

    TABULAR DATA OMITTED three types. Type 3 merchants (those seeking value) have

    the greater size, operate more in the hardware sector, and are generally affiliated.

    Management is often the responsibility of more than one person, but is less bureaucratic

    than in the other two types. More than two-thirds of businesses in type 3 have amanagement committee, and most tend to have more proactive and long-term strategies.

    The strategic decision-making process is usually shared.

    Type 2 firms (those favoring technological management) are evenly spread over the three

    retail sectors, but are more bureaucratic than type 3 firms. Their strategies are as

    proactive and the decision-making process is shared to a similar degree, but their time-

    frame tends to be shorter. Type 1 businesses (those making little or no use of

    technologies) have the fewest employees and are least likely to be affiliated to trade

    banners or buying combines. They operate mainly in the food sector. Management is

    generally the responsibility of one person, but these organizations are more bureaucratic

    than the other two types, and little use is made of management committees. They tend to

    be reactive, have a shorter time-frame, and the decision-making process is rarely shared.

    Overall, the more value- or performance-oriented the business, the more it will adopt

    many different technologies. In contrast, small retailers favoring technological

    management will favor business computing and implement a larger number of

    applications. The remaining majority (type 1) will opt mainly for POS and tele-computing (EDI).

    discriminant analysis was performed to establish the importance of each factor in

    determining a firm's being categorized as one of the three types. The results are presented

    in Table 6. The first variable to enter is the firm's managerial hierarchy (decentralization),

    followed by the firm's being in a less information-intensive sector (clothing or food).

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    Differences between types 1, 2, and 3 can also be explained by the firm's status, by the

    presence or not of a management committee, and by the administrative apparatus

    (structural complexity). The retailer's strategic orientation and time-frame are the last

    factors to enter in the analysis. These results are in line with the preceding ones and

    confirm the overall validity of the research model as eight variables display significant

    explanatory power.

    Table 6

    Discriminant Analysis of the Three Types of Firms

    Type 1: LOW TECH. Type 2: MANAGEMENT TECH. Type 3: VALUE

    TECH.

    Variable F to Wilks' Min. D.f.

    Step entered enter lambda p D(a) coef.(b)

    1 Man. hierarchy 6.0 .856 .004 0.2 .442

    2 Clothing (sector) 3.4 .781 .002 0.8 -.397

    3 Food (sector) 2.5 .728 .001 1.0 -.542

    4 Status 3.8

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    In recent years, small manufacturing enterprises have been implementing new

    computerized technologies at an every-increasing rate (Acs & Audretsch, 1990; Julien,

    Estime, & Drilhon, 1993), and the trend is being accelerated by international competition,

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    in particular by the opening up of national boundaries. However, the same urgency does

    not seem to exist in the commercial and service sectors, especially among independent

    retailers (Robertson & Gatignon, 1986; Treadgold, 1989; Julien & Thibodeau, 1991).

    Certainly, competitive pressure is relatively less intense in these sectors, or at the very

    least, certain small businesses have an advantage in terms of location, knowledge of their

    clients and their merchandise, or profit from niches created by market segmentation (for

    example, gourmet food stores or high fashion boutiques), They are thus under less

    pressure to become computerized; they may also be less likely to do so and may not

    believe new information technologies to be very useful because, for example in

    merchandise analysis, they know their customers and merchandise intimately.

    Many small retailers, though, whose ability to differentiate themselves from their

    competitors is limited, are feeling increasing competitive pressures, especially with thegrowth of chains and the advent of warehouse stores. A majority of these have neither the

    experience nor the financial resources required to plan, implement, and operate a

    computer-based information system (Raymond & Lorrain, 1992). But others have begun

    to systematically install new point-of-sales (POS) terminals or link up to wholesalers by

    tele-computing or electronic data interchange (EDI) (Sweeney, Putnam, Brooks, Hyde,

    Lee, Rubel, Rossiter, Armstrong, & Koenigsberg, 1990; Blili & Raymond, 1993).

    There may be many reasons for these behavioral differences, even among firms in the

    same industry facing the same type of market. In the manufacturing sector, macro-

    economic factors such as the rate of economic growth and the competitive structure of the

    industry can be determinant (Bouchut, Cochet, & Jacot, 1984; Julien & Thibodeau,

    1991). Researchers have also shown that more "technology-consuming" firms are

    distinguished from others by: greater profitability, the differential cost of new equipment

    (Mansfield, 1971, 1975; Khan & Manopichetwattana, 1989); the management profile or

    the owner-manager's personal characteristics (Miller & Toulouse, 1986); organizational

    complexity, centralization and formalization (Cohn & Turyn, 1980, 1984; Meyer & Goes,

    1987; Collins, Hage, & Hull, 1988); strategy type (Garsombke & Garsombke, 1989); and

    the quality of technological information obtained together with the capacity to process it

    (Blili & Raymond, 1993; Julien, Carriere, & Hebert, 1988; Gatignon & Robertson, 1989).

    However, very little research has been done on the reasons for new technology adoption

    in the service and retail sectors. To our knowledge, only Treadgold (1989) and Hogarth-

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    Scott and Parkinson (1990) have examined the question. Treadgold showed that

    differences in new technology adoption could be explained by the type of external

    organization (for example, between independent businesses and businesses belonging to

    groups) and the industry sector. Hogarth-Scott and Parkinson, for their part, showed that

    the limited use of EDI technologies among independent businesses stemmed from their

    fear of losing their independence. Miller, Glick, Yau-De, & Huber, (1991) have also

    indicated that organizations in the retail and service sectors have narrower ranges than in

    manufacturing on both technology and structure variables, and thus tend to exhibit

    weaker technology-structure relationships.

    The aim of this research, using empirical evidence, was to identify organizational,

    structural, and strategic factors underlying the level of penetration of various

    management, service, and information technologies among small retailers, including bothindependent businesses and those affiliated to trade banners or buying combines.

    Potential factors were identified from the previously cited literature, and in particular

    from Julien, Carriere, and Hebert's (1988) study done in the manufacturing sector.

    RESEARCH MODEL

    The research model is presented in Figure 1. A first set of factors, thought to influence

    new technology adoption in small retail firms, describes the structural sophistication of

    the firm in terms of centralization and complexity. In the organization theory literature,structure has often been characterized along these two dimensions or composite factors

    (Ford & Slocum, 1977; Miller, 1987). This includes prior research on the technology-

    structure relationship (Miller et al., 1991). Decentralizing and complexifying structure

    implies more elaborate communication, coordination, and control mechanisms; this in

    turn requires an infrastructure that can be better enabled through information technology

    (Huber, 1984; Leifer, 1988). Hence, more decentralized management and complex

    administrative structures should lead to greater adoption of information technologies by

    retailers (Cohn & Turyn, 1984; Miller & Toulouse, 1986; Raymond, Pare, & Bergeron,1993).

    The second set of adoption factors is strategic in nature, identifying the level of

    assertiveness, rationality, and interaction in business decision processes. These three

    factors have emerged in the strategy literature as fundamental dimensions or derivative

    constructs of the strategy concept (Miller, 1987; Venkatraman, 1989). The first

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    dimension refers to the proactiveness of decisions and risk taking. The second one

    concerns the planning and formulation of strategies. The third one refers to the

    political/bargaining processes that bear upon decisions. Information technology has

    become one of the key elements in the definition and realization of strategic objectives

    (Vitale, Ives, & Beath, 1986). In an increasingly complex environment, organizations

    must "align" their use of information technology with the implementation of their

    strategic decisions (Chan & Huff, 1993). Thus, when they are more proactive, more

    future/planning-oriented, and when more executives interact in strategy making, retailers

    would be more apt to implement computer-based information systems resulting from or

    in support of their strategy (Shrivastava & Grant, 1985; Schroeder, Gopinath, &

    Congden, 1989).

    The third set of factors thought to influence new technology adoption in small retail firmsare organizational, including size, sector, and status (independent or affiliated).

    Organization theorists have found the first two contingency variables to consistently play

    an important role in structure-technology-strategy relationships (Ford & Slocum, 1977;

    Miller et al., 1991). One expects larger firms to have adopted more sophisticated

    technologies (Dewar & Dutton, 1986; Raymond, Pare, & Bergeron, 1993). The same can

    be said of firms in more information-intensive retail sectors, e.g. hardware as opposed to

    clothing (Kimberly & Evanisko, 1981). Firms who become linked to banners or buying

    combines, as opposed to remaining independent, would also be greater users ofinformation technology (Tornatsky & Klein, 1982). The greater technological

    sophistication obtained by retailers who cooperate among themselves would tend to

    reduce environmental uncertainty in terms of markets and competitors (Huber, 1984).

    The seven factors of new technology adoption were chosen due to their fundamental

    nature as descriptors of structure, strategy, and organizational contingencies. These

    factors have also been identified as fundamental determinants of technology, both

    theoretically and empirically, and all have been used previously in the small business

    research context. Note that many of the organization theory and strategic management

    studies cited here point to the interdependence of strategy and structure, and to the

    contingent role of size and sector in this regard. However, given the focus and objectives

    of this study, expected interrelationships between structure, strategy, and organizational

    contingencies were not made explicit in the research model.

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    No distinction was made between management and production technologies as indicators

    of technological levels because in retailing, unlike manufacturing (Raymond & Pare,

    1992), it is difficult to differentiate the two. In addition, the actual level of independence

    or involvement in a group was not measured, even though some retailing groups (buying

    combines, trade banners, coops, franchises) exercise more control over their members

    than others. However, franchisees were excluded from the study because, in contrast to

    the other groups, their independence is very restricted (Castrogiovanni, Bennett, &

    Combs, 1993). In the Canadian province of Quebec, where the survey took place,

    independent retailers and members of buying groups or coops are responsible for more

    than 72% of all retail sales, at the expense of chains and megastores, whereas in the rest

    of Canada and in the U.S.A., their share is much smaller.

    RESEARCH METHODOLOGY

    The survey was carried out by collecting data from a sample of small retailers in the food,

    hardware, and ladies' garment sectors. Their names were obtained from the central

    business data bank of Quebec's commission on health and safety in the workplace

    (CSST). The survey was performed in two stages. First, 1,200 letters were sent out to the

    addresses provided by the CSST, requesting an interview with the owner (4.8% of these

    were returned due to improper addresses or out-of-business situations). Among the 232

    (19.3%) who were willing to cooperate, a total of 79 retailers were selected for semi-

    structured interviews in the field, with the help of a questionnaire. Using CSST data for

    the entire 1,200-firm population, the 79 firms were chosen on a stratified sampling basis,

    to be statistically representative of this population in terms of size and regional

    distribution for each sector. This was verified through chi-square and t tests. The

    questionnaire included 56 closed questions and six open questions, divided into four

    sections: the firm's demographics (size, status, etc.), structure, computer hardware and

    software, and strategy. A pre-test was done using three firms from each of the three

    sectors. Interviewing was deemed preferable to mailing the questionnaire, due to the

    technical or open nature of many questions, and to acquire more in-depth information.

    Two main types of technology were distinguished in the survey: hardware for business

    computing (computers), point-of-sales computing (computerized cash registers, whether

    or not linked to a central processing unit), and tele-computing (electronic links with

    outside firms, usually wholesalers); and software, assessed by the nature of the

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    applications portfolio. The measures of hardware and software technology adoption, i.e.

    the dependent variables, were adapted from previously developed instruments by Julien,

    Hebert, and Carriere (1988) and by Raymond and Lorrain (1992). Two main dimensions

    of structure--centralization and complexity--were assessed by measuring the managerial

    hierarchy (number of managers excluding the owners(s)/all personnel) and the

    administrative apparatus (clerical workers/all personnel), both measures previously

    validated and used in a small business context (Paulson & Stump, 1979). Complexity was

    also ascertained by the presence of a management committee (Julien, Hebert & Carriere,

    1988). The same was done with the three principal components of strategy, namely

    assertiveness, rationality and interaction. Miller's (1987) instrument was used to measure

    strategic orientation (or proactiveness: reactive-proactive) for the first dimension,

    organizational time-frame (or futurity: short-long term) for the second one, and strategic

    decision making (individual-consensual) for the third one.

    Table 1 shows the descriptive statistics of the research variables. Thirty-six percent of

    firms operated in the food sector (grocery stores, butchers, etc.), 40% in the hardware

    sector and 24% in the garment sector. They employed an average of 14.5 people

    (excluding owners), including 2.5 office staff. In all, slightly over 50% of the businesses

    were affiliated to a trade banner or buying combine, and 46% had a management

    committee. Strategically speaking, they were fairly proactive (4.0 on a scale of 1 to 7),

    had a medium time-frame (2.7 on a scale of 1 to 5), and shared the decision-makingprocess to a moderate degree (4.0 on a scale of 1 to 7).

    ADOPTION OF NEW TECHNOLOGIES

    The overall survey results show that 63 of the 79 firms questioned (79.7%) used at least

    one computer-based technology (i.e. electronic cash registers), a higher number

    TABULAR DATA OMITTED than the 71% forecasted by Collard (1989) for 1993 in the

    United States. The percentage is higher in the food sector (92.8%) than in the hardware

    (84.4%) and garment (57.9%) sectors. In all, 36 firms (46.2%) used only stand-aloneelectronic cash registers, 11 (14.0%) used cash registers linked to a central register, and

    16 (20.5%) had a cash register system linked to a computer. Eight firms (10.0%) had only

    a fax or telex, 31 (39.4%) maintained outside links by modem for batch data transfers or

    financial transactions (with banks), and 21 (26.9%) maintained systematic outside links

    through computers or terminals (EDI).

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    The number of business computing applications varied from zero to four. Eight firms

    (10.1%) indicated using four applications, 16 (20.2%) used three, ten (12.7%) used two,

    and four (5.1%) used only one application. In all, 41 firms (51.9%) did not use any form

    of business computing. Overall, the type of technology least used by sample firms turned

    out to be business computing and related applications. The other two technologies were

    more widespread, as only 15 firms (19.0%) did not have an electronic cash register (POS

    computing) and 18 (22.8%) did not have an electronic link with an outside organization

    (tele-computing). Table 2 summarizes mean adoption rates for each technology (using 5-

    point sophistication scales).

    DETERMINANT FACTORS OF NEW TECHNOLOGY ADOPTION

    Shown in Table 3 is the intercorrelation matrix of the independent variables. Given its

    highly significant relationship with five other factors, size was removed from further data

    analysis to reduce problems due to multicollinearity (Huang, 1970). The same was done

    with the decision-making variable, as it is strongly correlated with the other two strategy

    variables. Note that after removal of these two variables, two intercorrelations

    TABULAR DATA OMITTED greater than 0.3 remain, that is, firms in the clothing

    sector and firms with a larger bureaucracy (administrative apparatus) are less likely to

    have an affiliated status (r = -0.52, r = -0.35).

    As hypothesized, differences in levels of hardware and software technology adoption byretailers are due to a number of organizational, structural, and strategic factors.

    TABULAR DATA OMITTED

    Shown in Table 4 are the results of stepwise regression analyses on the four technology

    variables, revealing the determinant factors in each case. Retailers who adopt business

    computing are less likely to be in the food sector and tend to be affiliated to a buying

    combine or trade banner. They are more decentralized, i.e. show a higher ratio of

    managers (managerial hierarchy), and are more likely to have a management committee.

    Strategic factors do not seem to come into play here.

    The adoption of POS computing is determined by a different set of factors. Clothing

    merchants are less apt to employ this technology, as are firms with a larger ratio of

    clerical personnel (administrative apparatus). In addition, firms with POS technology

    have a longer organization time-frame. The use of tele-computing is mostly determined

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    by the retailer's status as member of a combine or banner, as expected. Firms who have

    implemented EDI are also more future-oriented than others, confirming Blili and

    Raymond's (1993) conjecture.

    Not surprisingly, hardware stores, with their greater information needs (e.g. for inventorymanagement), are the ones with the more extensive applications portfolio (software),

    while more decentralized firms implement a more sophisticated management information

    system. These results are in line with the technology-structure relationships found by

    Raymond, Pare, and Bergeron (1993). Also, more proactive and future-oriented retail

    firms implement a more extensive applications portfolio. This confirms the mutually

    determining impact of strategy and information systems in the context of SMEs (Blili &

    Raymond, 1993).

    Table 4

    Regression Analyses on the Four Technology Variables

    Standardized betas(a)

    HARDWARE SOFTWARE

    Business Point-of-sales Tele-

    Application Variable computing computing

    computing portfolio

    ORGANIZATION

    Size (removed initially)

    Sector

    Food -.22 -- -- --

    Hardware -- -- -- .22

    Clothing -- -.32 -- --

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    Status .36 -- .42 --

    STRUCTURE

    Managerial hierarchy .30 -- -- .28

    Administr. apparatus -- -.24 -- --

    Management committee .21 -- -- .23

    STRATEGY

    Orientation -