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Trang 3BOSTON UNIVERSITY
SCHOOL OF MANAGEMENT
Dissertation
PERFORMANCE EFFECTS OF CORPORATE DIVERSIFICATION: ROLES OF KNOWLEDGE RESOURCES, KNOWLEDGE MANAGEMENT CAPABILITY
AND INFORMATION TECHNOLOGY
By
HUSEYIN TANRIVERDI
M.Sc., London School of Economics and Political Science, London, UK, 1995 M.Sc., Middle East Technical University, Ankara, Turkey, 1993
B.Sc Middle East Technical University, Ankara, Turkey, 1989
Submitted in partial fulfillment of the
requirements for the degree of Doctor of Business Administration
Trang 4UMI Number: 3021065 Copyright 2001 by Tanriverdi, Huseyin All rights reserved ® UMI UMI Microforrn 3021065
Copyright 2001 by Bell & Howell Information and Learning Company All rights reserved This microform edition is protected against
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Trang 5© Copyright by
Trang 6First Reader Second Reader Third Reader Approved by Đ ˆ N Venkatraman, Ph.D
David J McGrath, Jr Professor of Management Information Systems,
Boston University School of Management
Chair of Dissertation Committee
Of Avi
C Henderson, Ph.D
ichard C Shipley Professor of Management Information Systems, Boston University School of Management
\od terre
Vasudevan Ramanujam, Ph.D
Associate Professor of Management Policy,
Trang 7PERFORMANCE EFFECTS OF CORPORATE DIVERSIFICATION: ROLES OF KNOWLEDGE RESOURCES, KNOWLEDGE MANAGEMENT CAPABILITY
AND INFORMATION TECHNOLOGY
(Order No )
HUSEYIN TANRIVERDi
Boston University School of Management, 2001
Major Professor: N Venkatraman, David J McGrath, Jr Professor of Management Information Systems
ABSTRACT
This dissertation studies how diversified firms add value to their businesses, and whether and how information technology (IT) contributes to the value creation process
Previous research posits that diversified firms add value by forming a portfolio of related businesses that enjoy resource-based synergies However, empirical tests of the relatedness hypothesis produced equivocal results: some studies found a significant link between related diversification and firm performance while others did not
Related diversification can lead to superior performance only if it is based on
Trang 8knowledge management capability, and IT knowledge relatedness of the firm Knowledge-based relatedness captures the extent to which the firm has a strategy of leveraging knowledge-based synergies across its businesses Knowledge management capability captures the firm's ability to implement a strategy of knowledge-based relatedness IT knowledge relatedness captures the extent to which IT human resources, IT relationships, and IT infrastructures of the firm’s businesses are managed in related ways
This study hypothesizes that the diversified firm adds value by creating and leveraging knowledge-based synergies across its businesses, and that IT enhances knowledge management capability and performance of the firm by facilitating exchange
of related knowledge resources across the businesses These hypotheses are tested with
primary data from senior business and IT executives of Fortune 1000 firms 339 business executives and 356 IT executives participated in the business and IT surveys of the study LISREL 8.3 is used to validate measurement and structural properties of the proposed research model
Trang 10TABLE OF CONTENTS
IBkU9)6V.9.86- :::::H Ả x 'Bk3/9)2/(60/42.5 Ơ XI lơi F29 6/2).0Ä1à9.40)010/060/9)15“ Ơ I
Conceptualization and measurement Of reÌat€CÏi€SS 5-7 sx x sen eegeeeereerrrreerze 2 Firm's implementation capabiÏIEV - - so nen g0 uc 4
(200 Tối G)šii (i00 21 4
CHAPTER I: THEORY DEVELOPMENT .0 -eecccceeceececeecceececseceeeeeeesnecesssceensceeses 8
Conventional wisdom on related diversification: Review and synthesis of previous work — H)ÄH)M),).) 8 93020 0v Am ố 8 Market relat€dn€ss .- - G55 SH ng nh ng na 9 Human resource reÌat€Ci€SS - - Gv nọ gọn nen ung 9 W ou vi 2e 10(2 o mẻ 9 Net 2185 11600: TỐ 12
Veracity and validity of the conventional wisdom: Is it enduring? -« «s=es 16 Inconsistent empirical findinS << « - si xnxx 16 Changing assumptions about products, markets, and competitIve logic 17 Performance implications of different types of relat€drness «sec cezsssee 19
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Research Questions - GÀ SH vn vn mg cư 20 Resource-based view of performance effects of related diversification - 22 Performance potential of tangIble resource-based relatedness . -~-c< 22
Performance potential of knowledge-based relatedness - - se se seeeree 23
Knowledge-based relatedness: Construct, dimensionality, and performance implications
— 24
Product knowledge relat€dne§Ss - - - ng HH ng xe 25 Customer knowledge relatedness «cv 211 ng cu vn 27 Managerial knowledge relatedn€sSsS 4s scn n ng my 28 Knowledge management capability: Construct, dimensionality, and performance 19119: Tố ốốốốốốốỐốốốẻẻốẻốốẻẻố 31 4Ị 2sei ã2ác ¡0 Bố ee ổ 33 Knowledge tranSÍ€T - - - - - ng TT HH me 33 6Ị 2c Hi v21: PA 34 614 si vi 0m ốố ố 34
Trang 11Su 1 — ).))).).).)HH.L Ả 50
is naậÝ 50
Power analysis and required sample SiZe .ccccccscseceeccsccessecscssesscessscceseccseasesensessees 52
Construct operationalization . sccscescesseccsscsseescesccscccseceecseesececeeacecsceasesesssacessrecsecens 53 MS) aăảa4 53 Tangible resource-based relatedness .ccccsccesseeeseesescescccesssessscecscececesecssesssncensecess 53 Knowledge-based relatedness «1.0.0 eeccesecsescsesneescesecccesscceecscecsecsscecscesereneesensenaecenece 56 Knowledge management capability - + St HH HH hcm gu ng cr 58
TT knowledge relat€Ci€SS - 5 + cv nh Hnt HH HH HH HT nu sec 60
Firm p€TÍOTIATIC€ - 2 + 2 + SE SE HH HT ng sac 61
90v aaậẽ Ồ 65
Development of SurVey instTUTT€TIES Q- S25 2S SH HH HH HH vn nre se 66 ltem development and t€StITIE, - - - 5< < 2< + S3 SH TK nh ng re 66 Scale development and f€StiTE -< + < cà SH HH CC HH nung nen cre 68
Informant competenCcy Im€aSUIFCS - << s4 xxx chư cư cưng ng 70
SPOMSOTSHID .dđdd4 71
Cover letter development and testing ecsscsscessesseescenccessscecsesscesceacsveceecsseeeesenses 72
Mailing list COrStTUCiOTI G5 <5 HH ng S nen cec 73
Identification of appropriate inÝOrTATILS .- 2 + 2 + czs SE cv ren re 75
'Web-based versions Of th€ SUTV€YS ĂQ SH vn HH HH gen sre sec 76 Summary of the strategies used for increasing response rate -.+sccsccec 78 Administration of the SurVey InIStTUITIS À G5 << SG SE ng ren ca 79
RESPONSE GP na 80
Analysis of non-respondenit Di4§ - -s + sx cv “TT n cưng ng nượn 80 Analysis of method bias .0 2 scsccscecsesseesceeeeesscesseescccsscecessecsscescereneeaseesesatsseesessacens 82 Assessment of informant cOmpe€t€n\Cyy - - s ssc HH ng na 84
CHAPTER IV: MEASUREMENT PROPERTIES OF CONSTRUCTS 2z 87
Knowledge-based relatedness: Dimensionality, convergent and discriminant validity 88 IT knowledge relatedness: Dimensionality, convergent and discriminant validity 98 Knowledge management capability: Dimensionality, convergent and discriminant
M5122 105
Predictive Validity - Ă se LH HT HH ngu 112
Reliability Of COTSITUCS << SH TH HH HH nung ng 112 0 810i 2bẠ TA 113
CHAPTER V: STRUCTURAL MODEL AND HYPOTHESES TESTING 115
Trang 12CC Nụn sv cv 001" 129 Analysis of strength of moderatiOn - - - < s-< sccx zsc HH HH cv re 129 AnalysIs of form Of mod€rtiOTI - <5 + + s< Ec c HC HE Em se 132 AnalySIS Of IIduUSfr ©ẾÍ€CS - 5s xxx cm HH n HH HH ng 134 Chapter 10((v0ý 2à NV rrdAAỖÐĐỖỎOỠỎOỎỒAÝ ,Ơ 135
CHAPTER VI: DISCUSSIONS OF FEINDINGS Ẳ 2 5 2S SH nen re 137
Performance effects of tangible resource-based versus knowledge-based diversification
—.1 Ơ 137 Interpretation of previous inconsistent findings on performance effects of diversification
— 138
Role of knowledge management capability for diversified firms . - 139 Role of information technology for diversified fir1ms . - 5 7< sec sec scrxecse 140 Validity of internal versus external measures of related diversification 141 Interpretation of the diversification discount puzZle .:ccssccssscssseceesseceseeeseeseces 143 Performance effects of firm versus industry leveÌ faCtOFS - 5< = << s=zczsce 144
0-/.3402.02i/409)i9003(0) 1510115 145
Theoretical Contributions .ceeccescessesssensceceeesssesecesssecsrecenscesencesneeeestecesseceeeessces 145
JSy1g14218aei0(51))0 5100 TA 147
li) su 3á440:u s00 TA" 147 New measurement scale for relatedness COnSfTUC - - 5 <5 Ă Sen sex cez 149 New approaches for ensuring sufficient response r4at€ - - < «s2 se ceecze 149
E2 t25sbiReauisi00 00v TA 150
FUUT€ WOIEK SH HH gu cư 152
APPENDIX A: CONSTRUCTS AND MEASUREMENT SCALES - 156 APPENDIX B: CODING GUIDELINES FOR IDENTIFICATION OF INFORMANTS
Trang 13LIST OF TABLES
HE CV hỏa án, hh 47
Table 2 2 Comparison of the conventional and proposed models of related
diversification-performance relatiOnShiIpD - - «se srsH.ng ng ng re ng re 49
Table 3 1 Sample size required in regression studies for power = 0.8 and alpha = 0.05.52 Table 3 2 Assessment of response bias: Respondents and non-respondents 81 Table 3 3 Assessment of response bias: Early respondents versus late respondents 82 Table 4 1 Measurement scale and purified items for knowledge-based relatedness 89 Table 4 2 Knowledge-based relatedness: Test of dimensionality of first-order factors 90
Table 4 3 Knowledge-based relatedness: ML, parameter estimates - «e5 95
Table 4 4 Measurement scale and purified items for FT knowledge relatedness 9S
Table 4 5 IT knowledge relatedness: ML, parameter estimates -s-««c<sess~se 105
Table 4 6 Measurement scale and items for knowledge management capability 106 Table 4.7 Knowledge management capability: ML parameter estimates lil Table 4 8 Predictive validity of COMStIUCtS cecccccsesesecceeeceeeesscscoseccccssecsesenseeees 112
IS LỄ: 600 \ A2áco ii ch .HH 113
Table 5 1 Summary statistics and correlation rmafFÏX - s52 5s c+< acc sex eexeezz 118 Table 5 2 Main effects of proposed CO'ISLTUC(S .- 2 B522 2+ S St v2 re crvec 122 Table 5 3 Tests of individual mediation hypoth€§S€S - 7< cS sec cre 123 Table 5 4 Test of the overall structural model: ML estimates of model parameters 126 Table 5 5 Test of direct effects: Comparison of alternative model specifications 128 I EU SN.NYL- cái ve 7a 129
Table 5 7 Test of strength of moderation: R@SuÏtS - 5 - + s ss se erzseersserrece 131
Trang 14Figure 2 Figure 2 Figure 4 Figure 4 models Figure 4 Figure 4 Figure 4 models Figure 4 factors Figure 4 LIST OF FIGURES
1 Performance effects of related diversification in the industrial economy 16 2 Performance effects of related diversification in the knowledge economy 47
1 Knowledge-based relatedness: Measurement properties of first-order factors
+2 th tt TT HT Họ Họ HH họ ch TH HT cu 93
2 Knowledge-based relatedness: Alternative first-order and second-order factor
—_ 111 96 3 IT knowledge relatedness: Measurement properties of first-order factors 100
4 IT knowledge relatedness: Alternative first-order factor models 101
5 IT knowledge relatedness: Comparison of first-order and second-order factor 102
6 Knowledge management capability: Measurement properties of first-order
+ 2h 1n Hà Hi HH 1 108
Trang 15CHAPTER I: INTRODUCTION
As we shift away from the traditional, relatively well-understood sphere of the industrial economy, we are required to rethink the underlying theories, concepts and assumptions that form the basis of understanding organizations The post-industrial economy—although labeled in numerous ways—is clearly focused on leveraging knowledge resources as a differential driver of value creation (Drucker, 1993) Within this general trend, there is a strong movement afoot to assess the validity and
applicability of many of the key concepts that served as the foundation of management principles These include the role of employment (Barlett & Ghoshal, 1997), value drivers (Stewart, 1997), organizational governance including the role of alliances and partnerships (Ashkenas, Ulrich, Jick, & Kerr, 1998; Gulati, 1999; Khanna, Gulati, & Nohria, 1998), and the role of information technology and information systems organization (Sambamurthy & Zmud, 2000)
This dissertation focuses on a central concept that has served as the basis for our understanding of the scope of firms, namely, corporate diversification Within business strategy and organizational research, researchers and managers have been concerned with developing a fundamental understanding of the limits and patterns of corporate
Trang 16with developing succinct links between diversification and corporate performance (Hoskission & Hitt, 1990; Ramanujam & Varadarajan, 1989)
Since the seminal work of Rumelt (1974), diversification literature has
hypothesized that related diversified firms outperform unrelated diversified firms The rationale for the relatedness hypothesis is that the overall value of the firm will be greater than the sum of the individual values of its businesses if there are synergies across those businesses However, empirical tests of the relatedness hypothesis have produced
equivocal results (Chatterjee & Wernerfelt, 1991) While some studies show that related diversification leads to superior performance, a considerable number of studies found no relationship between diversification and performance (Hoskission & Hitt, 1990; Robins & Wiersema, 1995) This dissertation identifies and subsequently addresses three factors which may account for the inconsistent findings: (a) weaknesses in conceptualization and measurement of relatedness constructs; (b) lack of measurement of firm’s capability to implement a strategy of related diversification; and (c) the neglect of the role of
information technology in firm’s capability to implement a strategy of related diversification
Conceptualization and measurement of relatedness
Trang 17competitive logic of the economy, the basis and strategic importance of various types of synergies are also changing Synergies that used to differentiate firm performance in the industrial economy may no longer be a differentiator of performance in a knowledge intensive economy Indeed, it has been pointed out that traditional related diversification constructs and measures capture relatedness of tangible aspects of firm’s resources rather than intangible aspects (Davis & Duhaime, 1992), and that the face and content validity of these constructs weaken when shifted from manufacturing to more knowledge- intensive service settings (Gassenheimer & Keep, 1998; Nayyar, 1992)
Building on the resource-based view of the firm, this dissertation argues that synergies arising from relatedness of tangible resources are still important for efficiency purposes but they can no longer differentiate firm performance in a knowledge-intensive economy because tangible resources are readily available to all firms in factor markets, and any advantage derived from diversification on tangible resources can be easily
observed and imitated by competitors In a knowledge-intensive economy, differentiators of performance are knowledge-based intangibles Therefore, this study proposes to
construe related diversification in terms of strategically important knowledge resources that are valuable, rare, imperfectly imitable and imperfectly substitutable It develops the knowledge-based relatedness construct to capture “the relatedness of strategically
Trang 18Firm’s implementation capability
Another potential explanation for the inconsistent findings on performance effects
of related diversification may be the omission of a critical mediator of this relationship,
namely, firm’s capability to implement a strategy of related diversification Related diversification per se only represents firm’s diversification strategy While a strategy of having related resources across businesses of the firm holds a potential for superior performance, it does not suffice to actually realize that potential The firm also needs a capability to implement its strategy in order to convert the performance potential of related diversification into actual performance results Most diversification studies focus only on the link between related diversification strategy and performance, and overlook whether the firm has the capability to implement a strategy of related diversification The absence of the implementation capability construct in research models may partially explain why some related diversifiers achieve superior performance while others do not
This dissertation specifies firm’s implementation capability as a mediator of the relationship between related diversification strategy and firm performance It argues that the firm can realize performance potential of its knowledge-based relatedness strategy if it has a capability to create and leverage knowledge-based synergies across its business units Therefore, it develops the knowledge management capability construct to capture “the degree to which the corporate headquarters of the diversified firm creates, transfers, integrates and leverages related knowledge resources across its businesses.”
The role of information technology
Trang 19knowledge resources across its related business units These processes increase communication and coordination needs across business units of the firm Information processing view of the firm hypothesizes that firms can meet the increasing
communication and coordination needs by increasing their information processing
capacity (Galbraith, 1973; Galbraith, 1977) Although this hypothesis has not been tested within the context of diversified firms, evidence emerging from IS research provides some indirect support for the information processing hypothesis Recent IS studies uncovered that diversification levels and performance of firms are significantly associated with their IT investment and IT usage levels (Bharadwaj, Bharadwaj, & Konsynski, 1999; Hitt, 1999) Within diversified firms, related diversifiers tend to invest more in IT compared to unrelated diversifiers (Dewan, Michael & Min, 1998)
Collectively, these findings indicate that IT plays an important role in diversification patterns and performance of diversified firms IS researchers interpret these findings from an information processing view, and infer that diversified firms invest in IT to meet communication and coordination needs across their business units However, much remains to be done to operationalize and test the information processing hypothesis in the context of diversified firms, and to understand whether and how IT reduces
communication and coordination costs across business units of diversified firms A complementary theoretical perspective on the role of IT in performance of diversified firms is provided by knowledge-based views of the firm Emerging
Trang 20Leidner, 2001) Some of the inconsistent findings on the diversification-performance relationship may be due to the lack of measurement of diversified firms’ IT capabilities in meeting communication and coordination needs and in managing valuable knowledge resources of the firm across business units Firms that lack the required IT capabilities may not be able to realize the performance potential of a related diversification strategy Therefore, it is important to include IT constructs in models of diversification-
performance relationships
Unlike the previous strategy and organizational research on diversification- performance relationships, this study recognizes the role of IT in the performance of diversified firms It asserts that diversified firms use IT not only for reducing costs but
also for creating value It argues that IT contributes to value creation in diversified firms
by facilitating exchange of related knowledge resources across business units Although the role of IT in reducing communication and coordination costs of diversified firms deserves research attention in its own right, this study focuses on the role of IT in value creation rather than cost reduction As the knowledge-intensity of the economy increases, competitive logic shifts from cost reductions to value creation through creation and deployment of knowledge-based intangibies While cost reductions through IT are still important for efficiency purposes, but they may not suffice for achieving superior performance
Trang 21will be able to create value by creating, exchanging, integrating and leveraging related knowledge resources across their business units JT knowledge relatedness refers to “the relatedness of processes used in managing IT human resources, IT relationships, and IT infrastructures of business units.” Relatedness of these IT processes enables seamless exchange of related product, customer, and managerial knowledge resources across business units of the firm
In summary, this dissertation takes a knowledge management perspective to study performance effects of corporate diversification By drawing upon and integrating
Trang 22CHAPTER I: THEORY DEVELOPMENT
This chapter develops a research framework for understanding the relationship between corporate diversification and firm performance in a knowledge intensive economy It begins by reviewing and synthesizing previous research on performance effects of related diversification It then assesses whether the existing related
diversification constructs and measures, which have been developed and refined under the assumptions of the industrial economy, are still valid and applicable in a knowledge- intensive economy After arguing for the need for new conceptualization and
measurement of related diversification constructs, it develops a new research framework,
which construes performance effects of corporate diversification in terms of knowledge
resources, knowledge management capabilities, and IT organization of the firm
Conventional wisdom on related diversification: Review and synthesis of previous work
Diversification has occupied a central role in describing and understanding the role of a corporation in the industrial economy Since Rumelt's (1974) seminal work, diversification literature has hypothesized that firms build on their resources to diversify, and that related diversifiers outperform unrelated diversifiers (Rumelt, 1974)
Traditionally, relatedness has been defined in four major ways: Product relatedness
A diversified firm is classified as product related if its businesses share similar
resources such as raw materials, production facilities, and product and process
Trang 23diversifiers by achieving scale economies in raw materials, facilities and technologies (Hamel & Prahalad, 1994; Rumelt, 1974)
Market relatedness
Market related diversifiers are those firms that operate in similar geographic markets; serve similar types of customers (e.g., industrial versus consumer); similar types of customer accounts (e.g., big versus small); and use similar distribution systems
(Capron & Hulland, 1999; Markides & Williamson, 1994; Rumelt, 1974; Stimpert & Duhaime, 1997a) Researchers argue that market related firms can gain advantage by sharing brand names, packaging, product design, pricing strategies, and advertising and distribution channels across similar markets (Davidson, 1983)
Human resource relatedness
Human resource related diversifiers are those firms in which occupational profiles of human resources (percentage distributions of employees by occupational categories) are similar across business units (Farjoun, 1994) If the sales of different businesses of a firm are concentrated in a group of industries that have similar occupational profiles, businesses of the firm are inferred to be human resource related (Farjoun, 1994; Farjoun,
1998) According to this approach, firms diversify into industries that have similar occupational profiles to their own (Chang, 1996), and human resource related
diversification provides advantages through sharing and transfer of human resources across similar industries (Farjoun, 1994; Farjoun, 1998)
Technological relatedness
Trang 24firms whose business units have related technological resources such as patents (Silverman, 1999) Technological relatedness approach also predicts that firms will diversify into industries in which their existing technological resources are likely to confer superior performance
Majority of diversification studies take an external view of firm’s relatedness They treat the firm as a black box They focus on either inputs or outputs of the firm to infer what is happening inside the black box For example, product relatedness focuses on
inputs to the firm Researchers examine the industries in which business units of the firm
operate If the business units operate in similar industries, as measured by standard industrial classification (SIC) codes, then researchers infer that products of the business units are related The assumption is that similar industries use similar inputs such as raw materials, equipment, and facilities in producing their products Market relatedness focuses on outputs of the firm Researchers examine if business units of the firm offer products in similar geographic markets; use similar channels for distributing the products, and serve similar types and sizes of customer accounts If they do, researchers infer that business units are market related
Clearly, both product and market relatedness constructs focus on relatedness of tangible aspects of products and markets Product relatedness emphasizes relatedness of
inputs such as raw materials, plant and equipment rather than relatedness of the
Trang 25accounts served rather than relatedness of the underlying customer knowledge across those markets such as customer needs, preferences, and purchase behaviors
Human resource relatedness and technological relatedness constructs aim to capture relatedness of some intangibles such as human skills and technological know- how However, they use indirect indicators at the industry level to infer relatedness at the firm level Hence, they suffer from a lack of correspondence between theory and
measurement For example, human resource relatedness is inferred from the similarity of occupational profiles across industry groups in which business units of the firm operates Two industry groups are considered to be similar if they employ similar percentages of engineers, managers, and other types of occupations Subsequently, business units operating in similar industry groups are assumed to possess similar human skills and know-how (Farjoun, 1994) By measuring similarity of percentage distributions of occupations across industry groups, this approach captures tangible aspects of the
relatedness of human resources across industry groups Since measurement of relatedness is at the industry group level and since it focuses on occupational profiles rather than actual skills, experiences, and know-how of human resources within occupational categories, it does not capture the relatedness of human skills and knowledge across businesses or how the firm deploys related human skills and knowledge across its business units to create synergies
Likewise, technological relatedness is measured by the similarities of patent filings and patent usage patterns across industries Firm level technological relatedness is
Trang 26(Robins & Wiersema, 1995) Since the industry level technological relatedness measures do not examine firm level technological resources or the inter-firm differences in
technological resource pools, they are at best capturing the relatedness of tangible aspects of a firm’s technological resources
In general, studies which conceptualize relatedness in terms of intangible resources, but operationalize them using industry level data suffer from a lack of correspondence between theory and observation Face and content validity of these constructs are weak (Nayyar, 1992) As Davis and Duhaime (1992) argue, measures based on SIC data tend to capture relatedness of tangible resources of the firm, despite the claims that they are satisfactory proxies for capturing the relatedness of intangible resources of the firms Therefore, this study refers to the traditional relatedness constructs reviewed above as capturing tangible resource-based relatedness One exception is
Silverman’s (1999) study, which used firm level patent data to operationalize the
technological relatedness construct However, not all diversified firms choose to use the patent mechanism for protecting their intellectual capital, and even if they do, some technological resources are simply not patentable Although Silverman’s approach may work well in technology and manufacturing intensive settings, its applicability to a representative sample of diversified firms, especially to those in service sectors, is limited
Moderating influences
Trang 27performance Performance ts initially positive but eventually levels off and becomes negative as diversification increases (Hitt, Hoskisson, & Kim, 1997; Markides, 1992) These findings might be explained by the presence of various firm and market level moderators, which are typically omitted in diversification studies
At the firm level, agency theory predicts that managers may diversify the firm to optimize their own interests rather than those of shareholders unless self-serving
Trang 28of effectiveness with which firms design and implement their governance mechanisms may moderate the relationship between diversification and performance
At the market-level, a broader set of contextual influences needs to be recognized For instance, the institutions taken for granted in advanced Western markets do not necessarily function well in emerging markets, where there are failures in product, capital and labor markets due to problems in information flow, misguided regulations, and inefficiencies in judicial and educational systems Therefore, firms in emerging markets may not gain access to technology, cheap financing, and sophisticated managerial know- how as easily as firms in advanced markets do To compensate for the resulting market failures, they may need to turn to diversification (related or unrelated), large firm size,
and large firm scope While unrelated diversification and large firm size and scope may
lead to failure in mature markets, they may well lead to success in immature markets (Khanna & Palepu, 1997) Hence, maturity of product, capital, and labor markets may moderate diversification-performance relationship
Trang 29turbulence, diversification is beneficial because firms derive benefits from synergy effects of asset specific investments across businesses When technological turbulence is high, firms may have to forego these synergy effects because they need to diversify into emerging technological fields Alternatively, they can diversify into less technologically turbulent contexts and continue exploiting synergy effects But both options reduce relatedness of firm’s existing technology portfolio, and hence, may affect performance negatively (Hoskission & Hitt, 1990) Finally, high competition intensity in a market leads to multiple choices for customers Diversified firms that offer multiple products and services are more likely to meet changing needs and preferences of customers When competitive intensity is low (e.g., a firm with a monopoly in the market), the firm may perform well without having to diversify its offerings to suit changing customer
preferences Therefore, diversification benefits may be greater in highly competitive
contexts
Trang 30Figure 2 1 Performance effects of related diversification in the industrial economy
Firm level factors Market level factors
eOwnership structure «Institutional maturity *Board composition *Market turbulence *Executive compensation *Technolo gical turbulence *Competition intensity Tangible resource-based relatedness Performance
Product related ness 5 *Marked-based
eMarket relatedness *Accounting-based
eHuman resource relatedness
*Technological related ness
Veracity and validity of the conventional wisdom: Is it enduring?
This study questions whether the conventional wisdom that is stylized in Figure 2.1 is still valid in a new economy, which has become more knowledge-intensive Based on the conceptual and empirical grounds discussed below, it argues that there is reason to believe that the conventional wisdom may no longer be sufficient for understanding performance effects of related diversification in the knowledge economy
Inconsistent empirical findings
Trang 31use of rigorous theoretical and methodological approaches to resolve the inconsistent findings
While theoretical and methodological rigor is important, the general concept of relatedness, its underlying constructs and operational measures also need to be rethought
in the context of a shift away from the industrial economy into an increasingly
knowledge-intensive economy where the nature and underlying assumptions of products, markets and competitive logic have changed substantively Existing relatedness
constructs and measures may not take these changes into account because majority of these constructs have been defined and refined at the heights of the industrial economy Even the most recently published diversification studies, which reflect the contemporary
thinking on related diversification, use data sets from early to mid 1980s (e.g, Silverman
1999; Farjoun 1998; Robins and Wiersema, 1995) Changes that have taken place in the past 20 years since then require at least an assessment of the veracity and validity of these constructs and measures
Changing assumptions about products, markets, and competitive logic In the industriai economy, products were assumed to be mass-produced, uniform, tangible outputs In the knowledge economy, ability to customize products to individual needs invalidates this assumption In the new economy, products are assumed to be non- uniform outputs containing tangible manufactured goods, which are fused with intangible embedded knowledge and a set of associated service activities (Pine II and Gilmore,
Trang 32offerings that adapt or respond to changes in the environment as they interact with consumers (Glazer, 1999)
In the industrial economy, markets were assumed to be homogeneous groups of customers with uniform demand characteristics (Brooks, 1995) whereas in the knowledge economy, each customer is assumed to be a market segment of one, who has distinct requirements to be fulfilled (Peppers, Rogers, & Dorf, 1999)
Trang 33Performance implications of different types of relatedness
In the industrial economy, an overarching assumption has been that any type of relatedness provides synergies and differentiates firm performance However, empirical findings indicate that not all types of relatedness are synergistic, and that the basis, synergy effects, and performance implications of different types of relatedness may change over time For example, in the pharmaceutical industry, strategic importance of production-based synergies across various chemicals declined as production costs
accounted for a small and continually declining share of the costs, and as differentiation- based competition moved center stage (Davis & Thomas, 1993)
In the knowledge economy, almost all sectors have gone through similar changes that have diminished the strategic importance of tangible resource-based relatedness In many cases, investments in intangible components of products and services (e.g., training of human resources, design, marketing, and service) outweigh expenditures on tangible components, and this trend is growing Advances in logistics, computer aided design, and communications allow firms to outsource tangible production work and focus on
intangible value drivers such as design of product, production, and process technologies
(Stewart, 1997)
Trang 34subsume the role of book-to-market ratio in predicting subsequent stock market returns (Lev & Sougiannis, 1999) As the basis of competition shifts from tangible resources to accumulation and deployment of knowledge-based intangible resources (Bettis & Hitt, 1995), synergy effects of tangible resource-based relatedness neutralize
Operational measures
From a measurement point of view, we need to recognize a corresponding shift Researchers have been generally comfortable with operational measures that have been developed and refined predominantly in manufacturing settings With the exception of a few studies, diversification researchers deliberately excluded knowledge intensive service industries from their samples (see Nayyar, 1992; 1993a; 1993b for exceptions) They calculated relatedness measures mainly by using SIC data, which tend to capture
relatedness of tangible rather than intangible resources (Davis & Duhaime, 1992) Since they use industry level data, tangible resource-based relatedness measures serve only as approximations of relatedness at the firm level Hence, SIC-based measures of
relatedness have little content and face validity as indicators of actual relatedness of firm’s business portfolio especially in the knowledge intensive economy (Nayyar, 1992; Robins & Wiersema, 1995) For example, in an empirical study of service firms, Nayyar (1992) found substantial differences between the performance implications of
approximate relatedness measures that are computed with SIC data and actual relatedness measures that are computed with primary data from the firms
Research questions
Trang 35sectors of the economy (Gassenheimer & Keep, 1998) There is need for new theories,
constructs, and operational measures in order to understand performance effects of
related diversification in a knowledge-intensive economy
This dissertation is based on two major arguments First, it argues that corporate
diversification and its link to performance should be construed in terms of knowledge
resources and knowledge management capabilities of firms in a knowledge-intensive economy Second, it asserts that Information Technology plays a central role in the creation and realization of knowledge-based synergies across business units of a
diversified firm It develops three new constructs Knowledge-based relatedness captures
relatedness of the underlying product, customer, and managerial knowledge resources of a firm’s businesses Knowledge management capability captures the firm’s ability to create, transfer, integrate and leverage related knowledge resources across its businesses IT knowledge relatedness captures relatedness of the underlying IT relationships, IT human resources, and IT infrastructure of the firm's businesses Using these constructs, this study develops and tests a research framework, which addresses three main research questions:
1 Does a strategy of knowledge-based relatedness differentiate performance of
the diversified firm?
2 Does knowledge management capability enhance firm’s ability to implement a strategy of knowledge-based relatedness by enabling creation and leverage knowledge-based synergies across business units?
Trang 36Resource-based view of performance effects of related diversification
Resource-based view of the firm provides a theoretical justification for shifting the focus of diversification research from relatedness of tangible resources to relatedness of intangible resources
According to the resource-based view, resources form the basis of related
diversification (Wermerfelt, 1984) Since most resources can be used in several products, they can serve as a source of related diversification (Wernerfelt, 1984), and influence diversification-performance relationship (Chatterjee & Wemerfelt, 1991) Resources are heterogeneous and imperfectly mobile across firms (Barney, 1991) Therefore, they are a potential source of superior performance (Barney, 1991; Conner, 1991; Peteraf, 1993) Due to variance in strategic importance of different types of resources, however, not all types of resource-based relatedness can provide superior performance Whether related diversification leads to superior performance or not depends on the degree to which underlying resources are valuable, rare, imperfectly imitable, and unsubstitutable (Barney, 1991) At any given time, a firm's resources are those tangible and intangible assets that are tied semi-permanently to the firm (Wernerfelt, 1984)
Performance potential of tangible resource-based relatedness
Trang 37resources are not likely to lead to sustainable superior performance (Spender, 1996) Benefits derived from diversification on tangible resources are easily observable and imitable Therefore, tangible resource-based relatedness cannot lead to superior performance
H1: Tangible resource-based relatedness is NOT associated with firm performance
Performance potential of knowledge-based relatedness
Intangible resources refer to firm-specific knowledge resources by which the firm adds value to incoming factors of production in a relatively unique manner (Spender, 1996) Knowledge resources may reside in individuals in the form of information, experience, insights, skills, know-how (Conner & Prahalad, 1996); in products, artifacts, or services (Hedlund, 1994); in technologies (Grant & Baden-Fuller, 1995); in patents (Almeida, 1996; Henderson & Cockbum, 1994); or in structures, rules, and procedures of the firm (Kogut & Zander, 1996; Nelson & Winter, 1982) Knowledge resources develop over long periods of time, through socially complex processes that span many
Trang 38Knowledge-based relatedness: Construct, dimensionality, and performance implications
This dissertation defines knowledge-based relatedness as the ‘degree to which underlying knowledge resources of a particular business of the firm are also applicable across other businesses within the firm.’ This definition recognizes that not all types of relatedness lead to superior performance It focuses on synergies arising from relatedness of strategically important knowledge resources rather than synergies arising from tangible resources, which may still be necessary for efficiency purposes, but no longer sufficient for superior performance
Knowledge-based relatedness is a multi-dimensional construct because firms may posses, and diversify on multiple types of strategically important knowledge resources Hence, specification of the dimensionality of knowledge-based relatedness requires identification of the most strategic knowledge bases that differentiate firm performance The three pillars of strategic thinking, i.e., products, markets, and processes, can serve as
a starting point in identifying the most strategic knowledge bases of firms (Gilmore &
Pine II, 1997a) Starting with these pillars, Kazanjian and Drazin (1987) proposed that relatedness could be analyzed by focusing on knowledge development in three primary functions of the firm: (a) product technology (engineering and R&D); (b) process
technology (manufacturing, materials, quality); and (c) marketing (market research, sales, promotion, customer service)
Trang 39processes as stabilized work routines cannot suffice to capture relatedness of underlying knowledge bases of the firm Therefore, as detailed below, this study redefines, expands, and transforms product, market, and process relatedness, and proposes product
knowledge relatedness, customer knowledge relatedness, and managerial knowledge relatedness as the three major dimensions of a firm’s relatedness In contrast to what is typically done in most diversification studies, this study focuses on strategic rather than operational level relatedness in all three dimensions (Grant, 1988)
Product knowledge relatedness
Product knowledge relatedness is defined as “the degree to which product
knowledge of a particular business of the firm is also applicable across other businesses within the firm.”
Product knowledge of the firm resides in its product and process platforms; human resources; and R&D and manufacturing alliances (Meyer and Lehnerd, 1997; Robertson and Ulrich, 1998; Sawhney, 1998; Inkpen, 1998) Product platform is a set of subsystems and interfaces that allow development and production of a family of
Trang 40especially tacit aspects of firm’s product knowledge such as the tradeoffs between distinctiveness and commonality of products, designs, production techniques, and technology applications (Robertson & Ulrich, 1998) Knowledge carried by human resources is one of the most important and durable drivers of business success (Hall,
1993) Product knowledge may also reside in R&D and manufacturing alliances of the firm as firms increasingly rely on strategic alliances for developing and producing their products (Inkpen, 1998)
Product knowledge relatedness can enable a diversified firm to share product
designs, subsystems, components, manufacturing processes, and human skills and
expertise across its business units Reuse of existing product knowledge reduces
development, tooling, and manufacturing costs, speeds up new product development, and
allows the firm to rapidly address new market opportunities (Meyer, 1997) Firms whose new offerings do not leverage existing product knowledge suffer from high costs and low