Examining Cumulative Capability Theory Ghana

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Examining cumulative capabilitiesin a developing economy

Kwasi Amoako-GyampahDepartment of Information Systems and Operations Management,

Bryan School of Business and Economics,University of North Carolina at Greensboro,

Greensboro, North Carolina, USA, and

Jack R. MeredithBabcock Graduate School of Management, Wake Forest University,

Winston-Salem, North Carolina, USA

Abstract

Purpose The purpose of this paper is to test the cumulative capabilities theory of manufacturingstrategy against the capabilities tradeoffs theory in a less-developed economy. It also aimsto test whetherthe sequential development of capabilities follows the same order prescribed in the sand cone model.

Design/methodology/approach Specific hypotheses on the relationships among the fourmanufacturing strategy components of cost, delivery, flexibility, and quality were stated. Data werecollected from 126 manufacturing firms in Ghana. Statistical analyses included correlation, factoranalysis, and multiple regression analysis.

Findings As with previous studies, the evidence here supports the cumulative capabilities theory.However, tradeoffs between the capabilities of quality, cost, delivery, and flexibility were not found. Inaddition, the sequence of capability development was found to be different from that in developedeconomies, with cost being second in importance after quality. This is postulated to be due to thesubstantially different economic conditions in Ghana.

Practical implications The findings of this research provide guidelines to managers, particularlyin developing economies, on the sequence of manufacturing capability development that is most likelyto occur as they seek lasting improvements in manufacturing performance.

Originality/value This paper provides findings from a less-developed economic environment thatis typically not included in manufacturing strategy research Ghana. The consistency of the resultswith those obtained in more advanced economies provides additional evidence for the cumulativecapability model.

Keywords Strategic manufacturing, Developing countries, Ghana

Paper type Research paper

IntroductionThe purpose of this paper is to test the cumulative capabilities theory (Nakane, 1986;

Ferdows and De Meyer, 1990; Noble, 1995; Flynn and Flynn, 2004) and examine the earlysequence of manufacturing capability development intended by firms in aless-developed economy such as that of Ghana. We thereby hope to also determine ifcapability development in suchan economy tends to follow a specific sequence similar toany of those found by other researchers.

Although there have been quite a few studies examining various aspects of thecumulative capabilities theory (Noble, 1995; White, 1996; Corbett and Whybark, 2001;Flynn and Flynn, 2004), most of the studies have been based on data collected from

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firms in advanced or rapidly advancing economies in North America, Europe and Asia.We have yet to see a test of the model in a less-developed economy such as that ofGhana. The practical importance of disconfirming either cumulative capabilities or thespecific sequence of attainment of capabilities is that managers in these countries may

be following the wrong production strategy without realizing it, thereby putting theirfirms, and perhaps even the delicate economy of these less-developed countries, at risk.As Grossler and Grubner (2006, p. 458) noted: capabilities are potential behaviormodes of a plant with which it can support and shape corporate strategy and whichhelp it succeed in the market place.

One of the earliest tests of the cumulative capabilities theory was the work done byNoble (1995). Using data collected from factories in Europe, Korea and North America,she concluded that there was general support for the cumulative capabilities theory ofoperations strategy. Her findings also indicated that there were differences in theapplicability of the model to different regions of the world. For example, although Nobleobserved that Korean firms tended to follow the Ferdows and De Meyer (1990) capabilitysequence of the cumulative model more closely than American or European firms, therewere several significant negative relationships between the capabilities, thus providingsome support for Skinners (1969) competing theory of tradeoffs among capabilities.

More recently, Flynn and Flynn (2004) used data from 167 manufacturing plantsfrom five countries to test the existence of cumulative capabilities. In contrast to Noble(1995), they found only positive relationships between the capabilities, thus providingsupport for the cumulative capabilities theory, but they did not find support for theFerdows and De Meyer (1990) sequential progression of capabilities. In addition, theyprovided evidence to show that differences existed in the patterns of cumulativecapability development between plants in different countries. Thus, it is apparent thatadditional studies on the cumulative capabilities theory are worthwhile.

In their original discussion of cumulative capabilities, Ferdows and De Meyer (1990)

noted that contingency factors might influence the sequence of capability development.Such contingency factors might include the business environment in the countries inwhich the firms are located, any technological advances, the presence of specialmanufacturing strengths, and any particular developmental approaches by the firms.Similarly, Flynn and Flynn (2004) identified other contingency factors such as whetherthere is experienced management and if there are underlying cultural factors thatmight lead to uncertainty avoidance. Thus, it appears that additional studies indifferent economic environments might enhance the theory and expand our knowledgeabout cumulative capabilities in practice.

Theory and hypothesesThe tradeoff theory

The cumulative capabilities theory was proposed as an alternative to the tradeofftheory in explaining the patterns of capability development by manufacturing firms.The concept of tradeoffs was advocated by Skinner (1969) who argued thatmanufacturing decisions and policies should be aligned with the competitivestrategies of the firm. In other words, it is important that manufacturing capabilitiesbe adjusted to match the overall objectives of the firm. This way, the manufacturingfunction offered the organization capabilities that allowed the firm to achieve itscompetitive advantage. These capabilities include cost, quality, dependability, speed,

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and flexibility (Hayes and Wheelwright, 1984; Leong et al., 1990). At the same time,Skinner argued that the firm needed to recognize its priorities and focus on a fewcapabilities at a time. This idea led to the tradeoffs concept.

All firms have limited resources. Thus, in order to achieve maximum impact

on organizational performance, the manufacturing function should focus on a narrowset of capabilities rather than all the capabilities simultaneously (Skinner, 1974).The argument was that firms focusing on a narrow set were more likely to achievesuperior performance than those that tried to emphasize all the capabilitiessimultaneously. From this reasoning, Skinner (1974) proposed the focused factoryidea with specific factories devoted to achieving excellence in a limited set ofmanufacturing tasks.

Although it is not the direct focus of this study, it is worth pointing out that thetradeoff theory, either directly or indirectly, has been the subject of several studies(St John and Young, 1992; Corbett and Van Wassenhove, 1993; Schroeder et al., 1996;Pagell et al., 2000; Safizadeh et al., 2000; Corbett and Whybark, 2001; da Silveira andSlack, 2001; Boyer and Lewis, 2002). For example, based on survey data collected frommanagers of plants that had implemented advanced manufacturing technology, Boyerand Lewis (2002) concluded that managers do make tradeoffs among competitivecapabilities. However, Safizadeh et al. (2000) found that there are tradeoffs betweensome capabilities (but not all) and that the choice of process, in particular, affects therelationships between the capabilities. For example, the tradeoff between cost andcustomization is often between plants with different process types, and Pagell et al.(2000) observed that, contrary to the assertions of Ferdows and De Meyer (1990),building cumulative capabilities might not be sustainable and that tradeoffs areeventually necessary. In general, the tradeoff theory has retained its importance inmanufacturing strategy research (Corbett and Whybark, 2001).

The cumulative capabilities theoryDespite the arguments for the tradeoff theory and the similarity of other concepts suchas Hayes and Wheelwrights (1979) product/process matrix, there were some researcherswho questioned its applicability. Most of the arguments against the tradeoff theory werebased on the successes of Japanese manufacturers. These researchers argued thatthrough the use of techniques such as JIT and flexible automation, the Japanese andother world class manufacturers were able to develop capabilities in several areassimultaneously (Schonberger, 1986; Collins and Schmenner, 1993; Hayes and Pisano,1996; Schmenner and Swink, 1998; Flynn etal., 1999).Other evidence against the tradeofftheory has come from the results of studies showing strong relationships betweenbusiness performance and multiple competitive capabilities (Cleveland et al., 1989; Rothand Miller, 1992; Vickery et al., 1993; Rosenzweig and Roth, 2004).

The argument that manufacturing capabilities should be, and frequently are,developed along multiple dimensions simultaneously led to the idea of cumulativecapabilities (Nakane, 1986; Ferdows and De Meyer, 1990; Noble, 1995; White, 1996;Boyer and Lewis, 2002; Flynn and Flynn, 2004). It has been further argued thatcumulative capabilities are more likely to lead to lasting improvements than capabilitiesthat are built at the expense of other (traded off) capabilities (Ferdows and De Meyer,1990). The cumulative theory allows managers to develop a proactive rather than areactive approach to capability development. To the extent that manufacturing

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proactiveness leads to improved business performance, one can expect the cumulativetheory to offer guidance for long-term lasting success (Ward et al., 1994).

At the same time, other researchers have hinted that the theories of capabilitytradeoffs and cumulative capabilities are not exactly mutually exclusive. Boyer and

Lewis (2002) noted that while plant managers consider simultaneously developingcapabilities in cost, delivery, flexibility, and quality as vital for competitive success,they also perceive the need for tradeoffs. Based on a longitudinal study of NorthAmerican manufacturers, Roth and Giffi (1995) observed that, although manufacturerscan improve along more than one capability at the same time, the rate of capabilityimprovement is not uniform, while da Silveira and Slack (2001) noted that practitionersdo not see tradeoffs in the same vein as academics. They view tradeoffs as a means tofocus and redirect attention to operational areas needing immediate attention(sometimes in the short-run) and not necessarily as a means of building up onecapability at the expense of another.

In an important reconciliation of the tradeoff-cumulative debate, Schmenner and

Swink (1998) and Clark (1996) proposed a theory of performance frontiers, whichbasically states that capabilities are typically cumulative for firms that are not on theleading edge of capabilities, but once on the frontier, only tradeoffs can then be made toalter the firms competitive position. This perspective has been advocated by otherresearchers as well (Hayes and Pisano, 1996). The practical implications of this insightare that leading edge (frontier) firms will have to make tradeoffs to alter theircompetitive position unless they can create an innovation that moves the frontier itself,such as the innovations Dell and Wal-Mart have created in their industries (Magretta,1998). However, firms that are not on the frontier can improve on multiple capabilitiesat the same time, as they strive to reach the leading edge in their industry.

That strong relationships exist between the different capabilities, howevermeasured, does not appear to be disputed. The meta-analysis done by White (1996)

shows the existence of significant positive relationships among quality, cost, delivery,and flexibility. Although the meta-analysis was based on individual dimensions of thecapability constructs, it does not take away from the central conclusion that boththeoretical and empirical evidence exist for the presence of cumulative capabilities. Theissue of interest here is if one should expect to find similar strong relationships forthe manufacturing environment in less developed economies, such as that of Ghana,where firms would generally not be expected to be on the frontier.

Ghana: a less developed economyThe domestic Ghanaian economy revolves around subsistence agriculture whichaccounts for about 34 percent of gross domestic product (GDP) and employs about

60 percent of the work force (The World Factbook: Ghana, 2005). Industrial outputrepresents about 25 percent of GDP and 15 percent of the labor force, withmanufacturing about 9 percent of GDP (The World Factbook: Ghana, 2005).

Since, 1983, and to the present time, Ghana has been implementing various types ofeconomic reforms that are aimed at reversing decades of economic decline. Most of thesereforms, which were undertaken in coordination with such financial institutions as theWorld Bank and the International Monetary Fund include trade liberalization, removalof price controls and government subsidies, floating of the domestic currency, and


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removal of all restrictions on imports, and were aimed at boosting productivity andincreasing export (United States State Department, 2005).

The economic liberalization policies have nurtured an open economy and haveminimized the hurdles that the manufacturing companies in Ghana need to clear in

order to obtain raw materials and other resources for productive activities. However, ithas created an unprecedented change in their business environment through increasedcompetition both in the domestic market and from imports into the country. Forexample, food processing and textile manufacturing output in 1990 were less than60 percent of their volume in 1977. Also, total manufacturing output for all industriesfell below the 1970s level for the first time in 1998 (Yusuf and Saffu, 2005). Moreover,the rate of growth of imports into the country between 1988 and 1999 was 7.3 percent,while GDP growth was only 4.3 percent (ISSER, 2002).

While the preceding economic factors might account for some of the reasons whyGhanaian manufacturing firms will not be on the performance frontier, there areadditional factors worthy of consideration. The Ghanaian manufacturing environment,

not unlike those of similar developing countries, is characterized by lack of access tomanufactured inputs, unavailability of human capital in the necessary skill areas (e.g.technicians and scientists), lack of access to capital, high transaction costs,demand/supply uncertainty, scale inefficiencies, and economic volatility (Frazer, 2005;Tybout, 2000). For example, the rate of inflation averaged 12.5 percent in 1999, rose to24.9 percent in 2000, rose again to 32.9 percent in 2001 and dropped to 14.5 percent in2002 (ISSER, 2002). Scale efficiencies are hard to achieve in periods of macro-economicinstability. In addition, changing regulatory reforms and demand uncertainties implythat firms are not likely to make long-term fixed capital investments that can lead toattainment of higher production efficiencies (Tybout, 2000). Thus, although themanufacturing sector grew by 3.7 percent in 2001, manufacturings share of real GDPhas remained constant at about 9.1 percent since 1996 (ISSER, 2002).

Thus, Ghanaian manufacturing companies need to develop and implementwell-conceived strategies in order to be competitive in the business environment. Thiswould include becoming more customer- and competitor-focused by developingstrategies to enhance product quality, reduce cost, build relationships with customersand suppliers, and enhance distribution and delivery of their products. Thesestrategies should be pursued in order to reduce operating costs, increase demand, anddeal with the heightened competition in the domestic market and increased importsfrom abroad (Yusuf and Saffu, 2005).

The increased import competition from world-class firms is not unique to Ghana. Ithas been observed in several different developing and emerging economies that haveimplemented world economy reforms (Khanna and Palepu, 2006; Dangayach and

Deshmukh, 2001). In Ghana and similar environments, the increase in competition iscompounded by the flooding of the market with used goods from the USA andelsewhere. The used goods include clothing (including shoes and home furnishingssuch as draperies), medical equipment, and spare parts for automobiles (Czaga andFliess, 2005). Take the case of used clothing. The exports of used clothing from theUSA alone to Africa grew from $35 million in 1989 to $109 million in 1999 (Maharaj,2004). Worldwide, exports of used clothing in 2001 was estimated at $990 million(Czaga and Fliess, 2005).

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The International Trade Center (based in Geneva) reports that Ghana imports over$43 million of used clothing every year. This contrasts with clothing exports of onlyabout $4 million a year (mostly socks). Thus, employment in the textiles industry hasdeclined from about 25,000 people to 3,000 (Crawley, 2004). Similar trends can be found

in other sub-Saharan African countries. Over 30,000 jobs have been lost in the textileindustry in Zambia in recent years (Rivoli, 2005). The African continent is graduallylosing its ability to clothe itself since manufacturers find it difficult to produce clothingat a cost that is as little as the equivalent of 10 cents that might be paid for usedunderwear discarded by Westerners.

Since, the domestic market is not very large or sophisticated, the increase in importsmeans that domestic firms must develop multiple and lasting capabilities that willallow them to survive in the local market as well as the international market. In theshort run, apparel manufacturers, for example, who focus on developing cost reductioncapabilities might be able to compete with the importers of used clothing as well asincreased competition from Asia (mostly China). However, their long-term survival willdepend on their ability to compete in the export market. Developing capabilities that

allow them to compete in the export market will dampen the effect of used goods andother imports on the domestic market. To summarize, due to the rapidly changingpolitical, institutional, and economic changes, it is important that firms in Ghana andsimilar environments, if they want to survive, upgrade and re-configure theirmanufacturing capabilities (Wright et al., 2005).

In order to succeed, firms have to invest in new equipment and technology, increasethe quality of their products and services, offer a diverse set of products to meetchanging customers needs, increase their productivity, and produce goods cheaply(Rankin et al., 2002). Given the poor state of manufacturing as well as the economicenvironment in Ghana, in accordance with the theory of performance frontiers (Clark,1996; Hayes and Pisano, 1996; Schmenner and Swink, 1998), we propose thatmanufacturing firms in Ghana will emphasize developing their capabilitiessimultaneously (rather than trade off one capability for another) in attempts to seeklasting improvements in their manufacturing competitiveness. In other words,Ghanaian manufacturers are so far within the performance frontier that one should notexpect any evidence of tradeoffs. As shown by Noble (1995), this can be confirmedthrough significant positive correlations among the emphases given to manufacturingcapabilities, as stated in our H1:

H1. There will only be significant positive correlations and no negativecorrelations among the manufacturing capabilities of cost, delivery,flexibility, and quality being emphasized by manufacturing firms in Ghana.

Sequence of emphasis on capabilities

Proponents of the cumulative model argue that not only are capabilities developedwithout trading off one for another but they follow a sequence of accumulation. That is,one capability is focused on and improved and then another is added to the mix whilecontinuing to improve the first capability, and then a third is added while improvingthe first two, and so on. So while capabilities cumulate, they follow a particularsequence. Although there are somewhat different variations of cumulative capabilitiessuch as Roths (1996) competitive progression theory, the one of special interest inthis study is the sand cone model of Ferdows and De Meyer (1990). The genesis of the


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sand cone model can be traced to the work of Nakane (1986) who argued that in order toachieve flexibility in their manufacturing operations, Japanese manufacturers shouldfirst emphasize quality followed by dependability, then cost, and finally flexibility.

Ferdows and De Meyer extended that idea and proposed the sand cone model where

each subsequent capability builds on the previous ones, so the capabilities cumulate.The analogy to the sand cone comes from the idea that a company continues its effortson the first capability even as it shifts its focus to improving the second capability, andthen continues to expand both the first and second capability as it turns its attention tothe third capability, and so on. Thus, the base levels gradually continue to expandwhile each upper level is added, similar to building a sand cone. However, based ondata from their 1988 survey of 167 high-performing European manufacturers, Ferdowsand De Meyer (1990) proposed a slightly different sequence from Nakane: quality at thebase, followed by dependability, speed (as a measure of flexibility), and last, cost.

There have been slightly different variations of this sequential capabilities modeltested ever since its inception. Noble (1995), for example, proposed the following

sequence: quality, dependability, delivery, cost, flexibility, and then innovation. Flynnand Flynn (2004) tested another slightly different sequence: quality followed bydependability, speed, flexibility, and cost. Several other sequence variations exist (Hall,1987; Swink and Way, 1995; Schmenner and Swink, 1998).

However, almost all of these sequences have quality at the base. In arguing forquality to be at the base, Ferdows and De Meyer noted that improvements in qualitycan lead to cost efficiencies (and also improvements in dependability and speed)whereas increasing cost efficiency, for example, is not likely to lead to improvements inquality. As an example, adoption of statistical process control mechanisms will ensurethat defects are detected early, thus reducing the number of bad quality products thatmight have to be re-worked or discarded, thereby reducing overall production costs.Similarly, having less rework will improve delivery lead times and attaining consistent

quality will lead to high-delivery capability.At the organizational level, several studies have shown a strong correlation between

quality improvement and business performance. After reviewing some of thesestudies, White (1996, p. 318) stated the positive impact of quality on businessperformance is well established, perhaps more so than the other capabilities. Giventhe importance of quality itself, in addition to its beneficial side effects on cost andperformance, it appears that quality has become what Hill (1994) refers to as an orderqualifier in the sense that products are not even considered for purchase if they do nothave high quality. The assertion that quality will form the foundation for cumulativedevelopment is not in dispute, based on the findings of the studies cited earlier.However, we also noted earlier that the Ghanaian market has been flooded with cheap

imports, putting immense pressure on manufacturers to reduce their prices. Thus, itmight be expected that the immediate pressure would be to reduce cost andsubsequently prices so as to compete with this flood of imports. Hence, a finding thatquality still forms the foundation for cumulative capability development even in theGhanaian environment would certainly make a contribution to the literature.Therefore, our H2 is:

H2. Emphasis on quality will form the foundation for cumulative capabilitydevelopment for manufacturing firms in Ghana.

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The original sand cone model has cost at the top of the cone, implying that whenstriving to achieve lasting improvements in manufacturing capabilities, costefficiencies are the last capability that should be emphasized after quality, delivery,and speed (as a measure of flexibility) in that order. However, in Ghana, the intense

competition brought about by market reforms and the resulting flood of cheap importsis forcing firms to emphasize developing their cost capabilities in order to competesuccessfully. We noted earlier the impact of used clothing on domestic apparel andtextiles production in the Ghanaian market (Crawley, 2004). In fact, this economicimpact is not limited to Ghana alone. Used clothes have led to the disappearance ofthousands of jobs in Senegal, South Africa, Tanzania, and Zimbabwe, among othercountries (Crawley, 2004). Nor is it limited to clothing the same pattern can be foundin shoes, furniture, home furnishings, appliances, and automotive components (Czagaand Fliess, 2005). For example, available data suggests that the cost of comparablegarden furniture imported from China is about 60 percent of that produceddomestically in Ghana (United States International Trade Commission USITC, 2004).

Also, there is the pressure of increased imports from Asia on the domestic market.The USITC notes that the growth in the textiles and apparel industry in Sub-SaharanAfrica is constrained by widespread shortages of raw materials and inputs, highproduction costs (compared to Asian producers), unused capacity, and outdatedequipment. The smuggling of inexpensive goods together with the influx of used goodsthat compete with local production hinder the competitiveness of local producers.

Whereas an emphasis on flexibility can be pursued when a firm is trying to shapethe direction of the market that it competes in, manufacturers in Ghana are not in aposition to shape the market. They are forced to seek cost reduction mechanisms thatwill allow them to be price competitive, all things being equal. Similarly, the logisticsand transportation infrastructure in Ghana is not well developed. Most people are usedto long delays of goods at ports or waiting long periods of time for receipt of goods. It is

not unusual for one personally to spend large amounts of time traveling short distanceswithin the Accra/Tema metropolitan area in Ghana because of the lack of parallel andmulti-lane roads. There is estimated to be only 43,000 kilometers of roadways in theentire country and less than 10 percent of these are paved (The World Factbook: Ghana,2005). Thus, developing capabilities in delivery is not likely to provide the samebenefits as would be expected from capabilities in cost and quality.

This line of thinking is consistent with the conclusions of Wacker (1996) who notedthat increased competition forces firms to focus on goals that have become orderqualifiers as opposed to order winners. Similarly, Swink et al. (2006) find that evenfor new product development, the best manufacturing firms also seem to developquality and cost first, and then speed later. In a meta-model analysis of manufacturingcapabilities, White (1996) proposed a model that shows direct linkages between cost

and business performance. He argued that such direct relationships may explain theattractiveness of cost reductions in gaining short-term business improvements.

We argue that in Ghana, the need to simply survive in the marketplace as a resultof the economic reform programs is forcing companies to develop capabilities in costefficiencies ahead of capabilities in delivery or flexibility. We note that this situation issimilar to the 1980s manufacturing environment in the USA where firms, because ofincreased competition from the Japanese, were forced to focus on both on quality andcost. In such environments, capability development in cost efficiencies ahead of


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flexibility (especially product flexibility) is highly recommended (Wacker, 1996). Thus,we propose that for Ghana, an emphasis on cost capabilities will immediately followthe focus on meeting quality requirements:

H3. Owing to import cost pressures on the Ghanaian economy, manufacturingfirms will emphasize cost capabilities after satisfying quality requirements.

Sample and data collectionThe data for this study came from a larger study that sought responses to questionnairesthat were hand delivered to 250 manufacturing and service organizations in Ghana.In addition to collecting data on the main study variables, we also collected demographicdata on the firms including industry type, size, fixed assets and ownership structure.The sample consisted primarily of large and medium-sized firms drawn from a list ofcompanies that are part of the Association of Ghana Industries and/or were listed in theGhana Business Directory. The study was confined to firms in the Accra-Tema

metropolitan area which is considered to represent the most important location formanufacturing activity in Ghana (Sohail et al., 2004; Rankin et al., 2002). Approximately,80 percent of all manufacturing enterprises in Ghana are located in the Greater Accraregion (Wolf, 2004).

Five graduate students in the School of Administration (the business school) at theUniversity of Ghana were given 50 questionnaires each and assigned to a specificlocality where a cluster of the service and manufacturing firms were located. Thestudents went to these companies and sought the operations managers or theirequivalent in the companies. An operations manager or equivalent is a senior levelofficial within firms in Ghana and thus he or she is in a position to provide strategiclevel responses. A typical title is production manager. In the larger study, separateportions of the questionnaire were given to marketing and human resource managers

within the company. There were several questions that were common to all sectionsand these were used to minimize self-report bias.

The students explained the purpose of the study, gave the questionnaires to therespondents, and obtained promissory dates when they could go back for thecompleted questionnaires. Sometimes, the students made two or three follow-up visitsto the respondents before receiving the completed surveys. One of the authors of thestudy also made random visits to some of the firms to check up on the completedsurveys as well as any uncompleted surveys. The entire data collection process tookthree weeks. This approach was used to ensure adequate and accurate responses sincefirms in Ghana are not used to mail-delivered surveys.

A total of 192 completed surveys were obtained representing a response rate of76.8 percent. Reasons given for the non-respondents included unavailability of the

individuals most qualified to complete the survey and lack of interest in participatingin the study. We checked for non-response bias by testing the size, industry type, andownership structure (Table I) and found no statistical differences between respondentsand non-respondents. Surveys from 12 firms were discarded due to incompleteinformation, resulting in a final usable sample size of 180 which included 59 servicefirms (deemed inappropriate for this study) and 126 manufacturing firms whichwere used here. Some of these firms sometimes had missing values in their responses.However, the few missing values were not substantial enough to require totally

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eliminating that firm from the database. Thus, in some of our statistical tests, thenumber of observations is slightly less than 126.

We took several steps to check for common method variance (CMV). CMV is theinflation of correlations between variables measured with the same method that oftenarises from self-report surveys. CMV arises because of respondents need to provideconsistent answers and/or answers that are socially desirable. First, as we indicatedearlier, this study was part of a larger study that included several different items

focusing on human resource, marketing, and competitive strategies in addition to theitems assessing operations strategy thatwereinterspersed throughout the survey.Second,someofthescaleswerereversedsooneendoftheresponsesdidnotalwayscorrespondtoalarger effect. Third, the respondents were assured of the anonymity of their responses aswell as given the assurance that their companies will not be individually identified in anypublished results. These techniques and others are established means by which CMVis minimized and have been used in published operations management research(Nunnally and Bernstein, 1994; Podsakoff et al., 2003; da Silveira and Arkader, 2007).

Industry No. of respondents Percent

Industry profileTextiles 10 7.9

Building materials 22 17.5Wood products 16 12.7Chemicals 22 17.5Metals 34 27.0Plastics 10 7.9Others 12 9.5Total 126 100.0

Number of employees Frequency Percent Less than 50 63 50.050-99 30 23.8100-199 16 12.7200-499 15 11.9500-1,000 2 1.6

Total 126 100.0Fixed assets, millions of Cedis a

Less than 500 17 14.0500-900 20 16.51,000-5,000 44 36.4.5,000 40 33.1Total 121 100.0Capital structureWholly local 80 65.0 Joint venture 27 22.0Wholly foreign 16 13.0Total 123 100.0Ownership structure family-owned businessYes 55 45.8

No 65 54.2Total 120 100.0

Note: aAt the time of this study one US$ was equivalent to 9,000 Ghanaian CedisTable I.

Demographics


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Last, we used Harmans (1967) one-factortest. Ourfactor analysis showing the presence offour distinct factors among capability variables provides assurance that CMV could notexplain the relationships among the variables.

VariablesSeveral of the empirical studies of both tradeoff and cumulative capabilities theorieshave directly asked managers how their performance on different dimensions of cost,delivery, flexibility, and quality compare with those of their competitors. The inherentassumption here is that if the managers indicate that the firm does well on a particulardimension, then it means it has developed capability in that area. Since, the goal of thisstudy was capability development, the questions were framed to elicit responses on theemphasis that respondents placed on various initiatives that allowed them to buildthose capabilities. We therefore asked managers the extent to which they haveinvested resources in various dimensions of cost, delivery, flexibility, and quality, theiranswers thereby indicating the degree to which they intend to build capability in thoseareas.

Following earlier studies (Ferdows and De Meyer, 1990; Noble, 1995), we includedmeasures of emphasis on both process-based quality (e.g. statistical process control,updating process equipment) and market-based quality (Flynn and Flynn, 2004), suchas improving product quality and reliability. Also, measures of emphasis on delivery,speed, and flexibility included faster deliveries to customers, meeting deliverypromises, handling changes in product mix, quickly adjusting capacity, and reducingmanufacturing lead times. Some of these measures, as noted earlier, can have effects onmultiple capabilities; for example, reducing lead time allows for both increasesin volume and variety to be achieved and thus contributes to building capability inflexibility as well as reducing costs and improving delivery (Noble, 1995).

Cost emphasis measures included inventory reduction and reducing material andoverhead costs (Ferdows and De Meyer, 1990; Noble, 1995; Flynn and Flynn, 2004).Overhead cost is clearly an important measure of the cost construct, even thoughfrequently ignored. For example, Ferdows and De Meyer (1990) found a very strongcorrelation between unit production cost and overhead costs. The recent emphasis thatfirms are placing on supply chain activities illustrates the importance of reducingmaterial costs.

Similar to Noble (1995), we use composite measures for the emphasis on the fourcapability constructs of interest here: quality, cost, delivery, and flexibility (Table II).However, it must be noted that there has been a lack of commonly agreed upondefinitions and measures for these constructs, as noted frequently in the literature(Corbett and Van Wassenhove, 1993; White, 1996; Ward et al., 1994; Flynn and Flynn,

2004). For example, the ability of manufacturers to respond quickly to customers(speed of response) is considered to be a measure of speed by Ferdows and De Meyer(1990), delivery by Noble (1995), and fast deliveries by Flynn and Flynn (2004).Similarly, manufacturing lead time (also speed of response) is considered to be anelement of delivery (Grossler and Grubner, 2006) and other times thought of as aflexibility measure (Ward and Duray, 2000). Thus, issues of reliability and validitybecome very important when one uses aggregated measures for the differentconstructs.

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Researchstudyauthors

Measures

FerdowsandDeMeyer

(1990)

Noble

(1995)

FlynnandFlynn

(2004)

GroblerandGrUbner

(2006)

C

urrentstudy

Processquality

Quality

Processquality

Conformancequality

Q

uality

Marketquality

Marketquality

Productqualityandreliability

Q

uality

Unitcost

Cost

Cost

Cost

Overheadcost

Cost

Cost

C

ost

Materialcosts

Inventoryturnover

C

ost

Productiondependability

Dependability

Dependability

On-t

imedeliverydependability

Dependability

Delivery

On-t

imedelivery

Deliveryreliability

D

elivery

NPDspeed

Speed

Speed

Speedofresponse

Speed

Delivery

Fastdelivery

Delivery

D

elivery

Speedofchangeofvolum

es

Speed

Flexibility

Volumeflexibility

Volumeflexibility

F

lexibility

Speedofchangeofprodu

ctmix

Flexibility

Productflexibility

Mixflexibility

F

lexibility

Table II.Comparison of factors

terminology andmeasures


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We assessed the reliability of our measures through the determination of Cronbach afor each construct. The Appendix shows the questions that were used to measure theemphasis on these variables and to collect demographic information. The itemsare very similar to others used in prior research (Ward and Duray, 2000). We indicate

the reliability based on the Cronbach a for each construct in the Appendix. Althoughone of them is near the 0.60 value, several researchers (Srinivasan, 1985; Nunnally andBernstein, 1994; Gupta and Somers, 1996) have noted that as of between 0.50 and 0.60are generally acceptable for exploratory (e.g. the Ghanaian environment) research.Last, Gupta and Somers (1996) argued that since a is a function of the number of itemsin the composite, it tends to be conservative; thus these a-values indicate acceptablelevels of reliability.

Construct validity was assessed in different ways. First, the fact that the itemscomposing our constructs were all from previous theoretically-based studies and didnot represent new scales provides evidence of the validity of the scales (Anand andWard, 2004; Swink et al., 2005). To verify that the questions were understandable toGhanaian managers, they were all reviewed by a University of Ghana business schoolprofessor and the MBA students who would eventually administer the surveys. Basedon their feedback, the questions were then reworded and clarified for a Ghanaianmanufacturing environment.

Factor analysis using principal component analyses with varimax rotation wasused to examine convergent and discriminant validity (Table III). We used varimaxrotation because it is the most common rotation method for exploratory research and

FactorMeasures Cost Delivery Flexibility Quality

Reducing material costs 0.791 0.181 0.182 0.194

Reducing overhead costs 0.809 0.142 0.028 0.159Reducing inventory costs 0.770 0.177 0.008 0.095Providing faster deliveries 0.256 0.674 0.301 0.156Meeting delivery promises 0.321 0.670 0.001 20.008Reducing manufacturing lead time 0.249 0.072 0.698 20.079Adjusting capacity rapidly 20.034 0.284 0.583 0.250Handling changes in product mix 0.108 20.321 0.770 0.217Using statistical process control methods 0.099 0.089 0.249 0.771Updating process equipment/technology 0.092 0.264 0.249 0.659Obtaining quality certifications such as ISO 9000 0.075 0.119 0.162 0.815Improving supplier quality 0.293 0.045 0.158 0.536Improving product performance and reliability 0.309 0.102 20.074 0.415Developing new processes for new products 0.047 0.234 0.145 0.680Developing new processes for old products 0.323 0.168 0.205 0.482

Making changes in product design as desired bycustomersa 0.290 0.351 20.147 0.304Handling variations in customer order and/ordelivery schedulea 0.205 0.357 0.021 0.294Reducing defect ratesa 0.322 0.247 0.364 0.353

Notes: KMO measure of sampling adequacy is 0.831; Bartletts test of sphericity significant atp , 0.001; n 122; athese items did not load strongly on any one factor and were eliminated fromthe scales

Table III.Factor analysis

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also because it is the rotation method that maximizes the potential that each variablewill load on one factor (Thompson, 2005). Convergent validity is typically considered tobe satisfactory when items load high on their respective factors. The results of ourfactor analyses are shown in Table II. All items had high loadings (greater than 0.40)

on their respective factors, signifying desirable measurement convergent validity.Items with multiple loadings and/or with loadings less than 0.4 were eliminated(Hair et al., 1998). Discriminant validity was assessed by examining whether each itemloaded substantially higher on the respective factor than on other constructs.The overall results indicated minimal cross loadings, signifying that reasonablediscriminant validity has been achieved (Table III).

Also, similar to the arguments used by Grossler and Grubner (2006), for cumulativecapabilities to exist we should see significant correlations between the differentcapability constructs. At the same time however, the constructs should be sufficientlydissimilar for discriminant validity to be present. The correlations between theconstructs (Table IV) are all significant but moderate (less than 0.7) providing furthersupport for discriminant validity; that is, the factors appear to be measuring distinct

concepts.

ResultsDemographic information on the firms is included in Table I. Data are provided aboutindustry distribution, firm size (number of employees and fixed assets), capitalstructure, and type of ownership. The largest industry category at 27 percent is metals.This includes fabricators of aluminum containers, cooking utensils, and otherappliances. The next group is chemicals (mostly pharmaceuticals) and buildingmaterials (iron rods, roofing sheets and concrete products) at 17.5 percent each. Woodproducts (mostly furniture) comprise 12.7 percent, followed by plastics (water tanksand plastic containers) and textiles at 7.9 percent each. The others category includes

paper, real estate construction, and information technology firms.The table also shows that half of the firms in the sample have less than50 employees. Firms with more than 100 employees are generally considered largewithin the Ghanaian manufacturing environment (Soderbom and Teal, 2001). Of thefirms, 65 percent are locally owned, with 22 percent being joint venture firms. Slightlyless than 50 percent of the firms are family-owned enterprises. Although we did not usea sampling procedure in identifying firms for the study, the distribution of firms in thevarious categories is identical to that of other studies such as Rankin et al. (2002) whoused a stratified sample of manufacturing firms in Ghana.

Similar to Noble (1995) and Flynn and Flynn (2004), we use correlations andmultiple regressions to test our hypotheses. If an emphasis on cumulative capabilities

Capability Mean SD Cost capability Delivery Flexibility

Quality 5.43 0.94 0.573 * 0.533 * 0.469 *

Cost 6.16 0.84 0.525 * 0.447 *

Delivery 6.22 0.94 0.315 *

Flexibility 5.39 1.00

Notes: n 122; *p, 0.001

Table IV.Means, standard

deviations, andcorrelations


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Dependentvariable

N

AdjustedR2

F

Independentvariables

Coefficient(standardizedb)

T

VIF

Quality

120

0.4

29

31.0

8***

Cost

0.3

13

3.6

3**

*

1.5

67

Delivery

0.2

95

3.6

2**

*

1.3

97

Flexibility

0.2

32

2.9

9**

1.2

60

Cost

120

0.4

12

28.9

9***

Quality

0.3

23

3.6

3**

*

1.6

15

Delivery

0.2

89

3.4

8**

1.4

08

Flexibility

0.2

03

2.5

6*

1.2

84

Delivery

120

0.3

45

32.6

3***

Quality

0.3

45

3.8

4**

*

1.4

84

Cost

0.3

28

3.6

4**

*

1.4

84

Flexibility

0.0

12

0.1

4

1.3

56

Flexibility

120

0.2

50

21.0

1***

Quality

0.3

12

3.2

4**

1.4

84

Cost

0.2

66

2.7

6**

1.4

84

Delivery

0.0

14

0.1

4

1.5

53

Notes:notsignificant;

*p,

0.0

5;

**p,

0.0

1;

***p

0.000

Table V.Relationships between

capabilities


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Discussion and conclusionsEvidence of cumulative capabilities exists within the Ghanaian manufacturingenvironment. Manufacturers in Ghana appear to emphasize all four competitivepriorities of low-cost, delivery, flexibility, and quality. We did not find any evidence

that manufacturers are trading off one capability for the other. Manufacturers inGhana are also implementing programs in statistical quality control, obtaining ISOcertifications, and implementing other quality programs to help develop capabilities inquality (Amoako-Gyampah and Gargeya, 2001). Simultaneously, they are emphasizingprograms that lead to reduction in materials costs, defect rates, manufacturing leadtimes, and capacity improvement so as to achieve unit cost efficiencies, and volumeand mix flexibility. Lastly, they are investing to achieve the capability of providing fastand consistent deliveries (Amoako-Gyampah and Gargeya, 2001).

The cumulative capabilities primarily emphasized by Ghanaian firms were qualityand cost. This is in contrast to findings from other environments. For example, Flynnand Flynn (2004) found that, for plants in Germany, most of the cumulative capabilities

were with dependability (delivery) and speed as opposed to cost and quality, whereasfor plants in the USA, the largest number of cumulative capabilities were dependabilityand flexibility.

The difference can, we believe, be linked to the Ghanaian manufacturingenvironment. As noted earlier, prior to the mid-1980s the manufacturing environmentwas characterized by large state run enterprises with their attendant inefficiencies andsubsidies. Following the implementation of structural adjustment programs, some ofthese enterprises were sold to private organizations, subsidies were eliminated, thecurrency was floated, and price controls removed. The resultant increase of importsmeant that locally produced goods were no longer competitive on price. Thisforced manufacturers to emphasize the development of capabilities in low-cost

manufacturing. Improving cost efficiencies and productivity is recognized as veryimportant because of increased competition in the domestic market (Wolf, 2004). Thefirms are therefore emphasizing inventory reduction and reducing overhead andmaterial costs. The cost of materials, in particular, is of greatest concern because about50 percent of all raw materials used in production in Ghana are imported (Wolf, 2004).

In Ghana, there is also the perception that foreign goods are of higher quality thanlocally manufactured goods. Thus, in order to compete firms have to developcapabilities in quality, as stated earlier. This is consistent with the findings of Khannaand Palepu (2006) who noted:

. . . we have found that once emerging market firms improve the quality of their products andservices, they are able to cater to customers at home as well as, if not better than,multinational companies.

We also note that in the mid-1980s, manufacturers in the USA were similarly forced tofocus on both cost and quality in the midst of increasing imports into the USA marketfrom Japanese manufacturers.

There are, of course, limitations to our study. We did not test for the impact ofcapabilities on firm performance. It will be useful for future studies to examine therelationship between capability development and firm performance. A study thatincorporates a time lag between capability development and performance would be

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particularly useful. This should help managers understand which programs toimplement first in order to improve performance (Corbett and Whybark, 2001).

The fact that over 75 percent of our firms have less than 100 employees limited ourability to asses the impact of firm size on capability development. Also, although the

study was confined to manufacturing firms, it would be interesting to ascertain ifdifferences exist between different manufacturing industries.

Since, this was a cross-sectional study we cannot infer cause and effect in terms of thedependencies between the capabilities. However, our data suggest that our threehypotheses cannot be rejected and that capability development based on manufacturingemphasis thus appears to largely follow the sand cone model, though the sequence issomewhat different from that suggested by Ferdows and De Meyer (1990). In Ghana itappears that the sequence is quality followed by cost, and then delivery and/orflexibility. This research has contributed to the literature on the cumulative model ofoperations strategy by providing findings from a non-traditional environment themanufacturing environment in Ghana, an underdeveloped economy. Previous studies ofthe cumulative model have been based on advanced or rapidly developing economies.We provide findings from an emerging economy and by providing support for thosefindings we contribute to the strengthening of the theory on cumulative capabilities.

Lack of talent and access to capital (compared to companies in the USA and Europe)make it difficult for firms in developing countries to build global brands or invest intechnology to achieve flexibility in their operations (Khanna and Palepu, 2006). Inaddition, emphasizing reliable and dependable delivery is not easy to achieve becauseof inadequate infrastructure and delivery systems. Despite the relatively low-cost oflabor, most manufacturers are unable to produce items cheaper than the landed price ofequivalent imports. Our recommendation to managers in such environments is to focuson developing capabilities that have been known to lead to lasting improvements.

Our findings as well as those of others (Flynn and Flynn, 2004; Noble, 1995) clearly

indicate that differences exist in the patterns of cumulative capability development. Wehave used the economic environment prevalent in Ghana to explain our results. Itwould be worthwhile to develop theoretical extensions to the sand cone model thatincorporate specific economic factors into the relationships between capabilityvariables. Such models would enhance our ability to predict and explain the impact ofcumulative development in different economic environments.

Additionally, our sample included firms that in other environments (such as in theUSA) might be considered to be very small (50 percent of our firms had less than50 employees). It appears from our findings that even small firms develop capabilitiesin a cumulative manner. Given that the argument for tradeoffs and cumulativecapabilities is still ongoing, this study provides support for the cumulative model in anon-traditional environment. Whereas in the past, domestic producers might have

leaned on government policies and other covert activities, such as burning down usedclothing markets (Rivoli, 2005), it appears that developing capabilities that allow themto produce for export is gradually being recognized by manufacturers in Ghana asmore a effective approach to sustainability.

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Appendix. Capability scales used in researchPlease indicate the degree of emphasis that your manufacturing plant places on the followingactivities (rated on a seven-point scale 1 no emphasis to 7 extreme emphasis):

Cost (a 0.74). reducing material costs;. reducing overhead costs; and. reducing inventory.

Delivery (a 0.74).

providing faster deliveries; and. meeting delivery promises.

Flexibility (a 0.59). reducing manufacturing lead time;. handling changes in product mix; and. adjusting capacity rapidly within a short period.

Quality (a 0.79). using statistical process control methods;.

updating process equipment/technology;. improving product performance and reliability;. obtaining quality certifications such as ISO 9000;. improving supplier quality;. developing new processes for new products; and. developing new processes for old products.


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Demographics: check the industry to which your company belongsIndustryA Food A Building materials A Textiles A PrintingA Electronics A Transportation equipment A Rubber A ServicesA

ChemicalsA

Wood productsA

MetalsA

Other__________Indicate the number of employees in your companyA Less than 50 A 50-99 A 100-199 A 200-499 A 500-1,000 A More than 1,000

Indicate your companys fixed assets (in Cedis)A Less than 5 hundred million A 5-9 hundred million A 1-5 billion AMore than 5 billion

Indicate the capital structure of your companyA Wholly local A Joint venture A Wholly foreign

This company is a state-owned enterprise.A Yes A No

This company is a family-owned enterpriseA Yes A No

Corresponding authorKwasi Amoako-Gyampah can be contacted at: [email protected]

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