Perspectives on Various Issues of Interest

The Product Quality Impact of Aligning Buyer-Supplier Network Structure and Product Architecture

There has been a trend, in the last decade, of buyers outsourcing new product development (NPD) activities to suppliers. In a study my co-authors and I examine the impact of (mis) alignment between buyer-supplier network structure and product architecture on two product development outcomes: product quality and product recalls. The hypotheses are tested on a uniquely assembled database of supplier networks of automakers for 12 vehicle systems. The results suggest that while dense supplier network are associated with higher future product quality and lower future recall magnitude, structural holes are associated with lower future product quality and higher future recall magnitude. Further, the results suggest that product quality partially mediates the relationship between supplier network characteristics and recall magnitude. Interestingly, these effects are significantly moderated by the product architecture. While network density is positively related to product quality of weak design interfaces (i.e., modular systems), structural holes in the supplier network are positively related to product quality of strong design interfaces (integral systems). The results offer valuable insights to managers about the appropriate supplier network structure for superior quality.

The conceptual model for the study is as follows:

A sample network is as follows:

The findings of this study offer numerous valuable insights for managerial practice. In recent years, there has been increased emphasis on improving supply chain performance. The emphasis has been using concepts such as modularization, flexible manufacturing, and lean versus agile manufacturing to boost performance. Despite such advances, the poor performance of supply chains, as evidenced in growing number of product recalls in the marketplace, continues to frustrate and disenchant managers. Our study shows that mismatch between structure of buyer-supplier networks and product architecture aggravates crises such as product recalls.

We find that network density and structural holes have different effects on recall outcomes. Dense supplier networks are associated with superior outcomes such as better quality and lower magnitude of recalls whereas supplier networks with structural holes are associated with greater recall magnitude. The implication for buyers is that they ought to encourage its suppliers to forge ties with each other and facilitate exchange and sharing of information. For example, a supplier facing a quality problem with the root cause not known can benefit from the exchange of solutions from the supplier network. Although maintaining a dense supplier network is costly, the information exchange benefits are significant especially when buyers farm out important processes such as product design and manufacturing to suppliers. In contrast, structural holes in a supplier network increase the magnitude of recalls experienced by buyers.

Importantly, our findings caution managers to refrain from viewing dense supplier networks as beneficial and supplier networks with structural holes as detrimental for quality. Our findings, instead, point to the need to evaluate the normative supplier network structure in conjunction with the architecture of the product. The findings suggest that dense networks are beneficial for weak design interfaces (modular systems) than for strong design interfaces (integral systems). As noted before, when buyers outsource design and manufacturing of modular systems, they cede control to supplier networks. Thick ties between suppliers facilitate coordination and information exchange and ensure that buyers are able to meet varying downstream demand without compromising the quality of weak design interfaces. In contrast, structural holes in supplier networks are more beneficial for strong design interfaces than for weak design interfaces. Buyers need to be located centrally in supplier networks and mediate information flows between suppliers to ensure that the quality of integral systems does not degrade.

We performed a univariate transfer function analysis to better understand the economic value of matching buyersupplier network structure and product architecture. We computed the direct impact of a one standard deviation (S.D.) increase in network density and structural holes in the supplier network on quality and recall magnitude. We evaluate this relationship for strong and weak design interfaces. The high and low levels of SDI are set at the +1 S.D. and −1 S.D. from mean values of the variable, respectively. To compute the dollar impact of decrease in recall frequency because of matching, we turn to previous research that has assessed the shareholder value destroyed by product recalls. Barber and Darrough [6] note that on average a product recall in the automobile industry eroded shareholder wealth by $72.99 million. This amounts to $125.62 million in 2011 dollar terms. Our post hoc analyses reveal that a 1 S.D. increase in network density increases economic value by $29.85 million at low levels of SDI and decreases economic value by $106.41 million at high values of SDI. The total economic value was destroyed because of a mismatch between supplier network density and product architecture is $136.26 million. While dense networks are costly to maintain because of higher number of ties and greater information flow, our findings show that the economic value of dense ties in supplier networks is quite substantial. Similarly, a 1 S.D. increase in structural holes increases economic value by $219.31 million at high levels of SDI and diminishes economic value by $14.27 million at low levels of SDI. The total economic value was destroyed because of a mismatch between structural holes and product architecture is $233.59 million. Cumulatively, mismatches between supplier network structure characteristics and product architecture destroy the buyer’s shareholder wealth to the tune of $369.85 million on an annual basis. The following table summarizes the economic implications of our findings:

Source: Kalaignanam, K., Kushwaha, T. and Nair, A., 2017. The Product Quality Impact of Aligning Buyer-Supplier Network Structure and Product Architecture: an Empirical Investigation in the Automobile Industry. Customer Needs and Solutions, pp.1-17.

Assessment of supply chain integration and performance relationships

The concept of integration has received considerable attention in operations and supply chain management literature in a time spanning over two decades. To advance theory development, it is important to critically examine the empirical findings in various integration studies. In a recently published paper my co-author and I undertake an extensive investigation of the relationships between supply chain integration and various performance dimensions using a metaanalytical methodology. The study contributes to literature in four important ways. First, the findings empirically show that internal integration, supplier integration, and customer integration have significant impact on a firm's financial performance. Second, the study examines the impact of internal integration, supplier integration, and customer integration on a firm's operational performance; and its underlying dimensions of cost, quality, delivery, and flexibility separately. Third, the study points out the specific relationships between supply chain integration and performance that need to be further examined within contingency framework to discern the role of moderating factors. Finally, to provide direction for managerial decision-making, the study offers insights regarding integration dimension(s) that have largest breadth and depth of impact on various performance measures.

The study provides some insights for practitioners that are engaged in managing operations within their organizations as well as in the extended supply chain. Firms typically have limited resources and managers need to allocate these resources prudently to obtain maximum possible benefits. Supply chain integration requires monetary investments to set up the necessary infrastructure. This study provides some guidance for managers so that they can make decisions regarding integration investments based on the chosen competitive priorities. The investments allocated for integration could be targeted towards, and prioritized upon, the relevant dimensions of supply chain integration depending on the desired performance outcomes. Internal integration should generally precede external integration since it is important for the processes within an organization to be aligned before engaging in information sharing and collaboration activities with external supply chain partners. Managers should consider this sequence when they are making supply chain integration related decisions if the depth of impact is considered. Additionally, we find that supplier integration has the maximum breadth of impact (83.33%) followed by customer integration (66.67%) and customer integration (66.67%).

Moreover, managers should be aware of the contextual differences in the relationship between supply chain integration and performance. The findings of this study lend support to certain moderating effects that might be strengthening or weakening the relationships between supply chain integration and performance. The context should be carefully analyzed and studied before making potentially expensive and hard-to-reverse investments in integration. For instance, environmental uncertainty stands out as a critical issue to be considered when it comes to supply chain integration. Information processing becomes more crucial in highly uncertain environments relative to others, and managers should be cognizant of the requirements of the business environment they operate in when they are making supply chain integration decisions to align the degree of coordination internally as well as externally. In essence, managers should supplement their bandwagon-driven or benchmarking-driven integration initiatives with prudent consideration of their own contextual environments.

Source: Ataseven, C. and Nair, A., 2017. Assessment of supply chain integration and performance relationships: A meta-analytic investigation of the literature. International Journal of Production Economics, 185, pp. 252-265.

STRUCTURING SUPPLIER INVOLVEMENT IN NEW PRODUCT DEVELOPMENT: A CHINA-US STUDY

In a recently published paper, my co-author and I examine how three types of inter-group structures - administrative (formalization and centralization), task (task interdependence) and physical (co-location) - influence project performance and buyer learning in NPD projects. Buying and supplying organizations rely on each other for developing better products in an efficient manner, which explains the popularity of involving suppliers in new product development (NPD). However, such involvement is not always successful, partially due to the challenges of structuring a buyer-supplier team to manage joint dependence and dependence asymmetry. adopting a contingency theory perspective, we study whether the national context moderates the effects of inter-group structures on project outcomes. We adopt a two group structural equation modeling approach to test hypotheses with survey responses from a sample of NPD projects in the United States (US) and China. 

Survey responses from original equipment manufacturers (buyers) are used to test the hypotheses. The initial set of respondents comes from a commercial list provider who provided contact information of 2045 US-based company managers. Among this initial set, 2000 have email addresses and 45 have mail addresses. The initial set of respondents in China was extracted from member listings of manufacturer associations with a sample size of 580, all of which provided physical mailing addresses. Job titles and industries are used to screen respondents. Specifically, we limit the initial set of respondents to those that have responsibilities in the areas of engineering, manufacturing, product development, project management, or purchasing, which have been shown to be relevant for NPD projects. We limit industries to those that manufacture physical and discrete products and avoid service and software companies due to their significantly different innovation inputs, processes, and outputs. We adopted both electronic and hard-copy mailing approach for data collection. We hosted a two-part survey on Survey Monkey. The overall response rate for completed pairs of Part I and II surveys are 16.23%. Specifically, 186 completed surveys were collected online from the US out of 2000, indicating a response rate of 9.3%; 28 completed surveys were collected in mails out of 45 from the US, indicating a response rate of 62.2%; 212 completed survey were collected in mails out of 580 from China, indicating a response rate of 36.6%. 

All the constructs are measured using existing scales. In order to control for measurement errors, we adopted the two-group Structural Equation Modeling (SEM) approach to test whether effects of the four structural factors on project performance and buyer learning differ significantly between China and the US. The research model is as follows:

Our results show the importance of taking a national contingent view when studying the performance implications of inter-group structures in NPD projects. We found both similarities and differences between the two countries regarding how inter-group structural factors impact project performance and buyer learning. The effects of task interdependence, compared to those of other structural factors, seem to be least country contingent. All other structural factors differ significantly in influencing project performance and/or buyer learning between China and the US. Specifically, the results from our study show that colocation enhances buyer learning only in China and not in the US. This emphasizes the importance of considering the congruence of China’s national context, which values collective behavior, with the opportunities presented by colocation, when studying how co-location influences project outcomes. Similarly, we found that formalization inhibits buyer learning in China but not in the US. The rules and procedures within a formalized structure of NPD projects constrain the natural tendencies of engaging in informal knowledge exchange among Chinese team members. Since formal rules and procedures are the way of professional life in the US, the constraining effects on buyer learning are not significant. Among the four structural factors examined, centralization differs most between China and the US in its performance implications. Due to its congruence with China’s power distant culture, socialistic ideology and informal institutional environment, a centralized structure hurts buyer learning more in the US than in China. However, contradictory to our hypothesis, centralization is found to hurt project performance more in China than in the US. This unexpected result might suggest the importance of considering the types of project goals when examining the effects of centralization. For more task-oriented goals, such as project performance, the comfort of working in a centralized inter-group structure (in China’s case) might amplify the damaging effect of centralization due to a lack of urgency to correct the counterproductive mechanisms. This could endanger the accomplishment of immediate tasks and thereby hurt project performance.

In summary, these significant differences between the two countries show that the national context, as a multi-dimensional variable, could significantly influence performance implications of inter-group structure in interorganizational NPD projects. These impacts could result due to different reasons, such as culture, ideology, and institutions, which present challenges in terms of measuring the exact intervening variables. Data from the US and China allows us to consider these facets to be subsumed within the national context and examine how various factors, together, might create contextual limits (or opportunities) for structuring interorganizational NPD projects. The context-dependent relationship of inter-group structure with project performance and buyer learning lends credence to the equifinality argument. Specifically, there are multiple ways in which structural elements can impact project performance and buyer learning and, depending on the underlying context, different structural arrangements can provide various pathways to improve NPD project performance.

By considering both project performance and buyer learning, our study highlights the multi-faceted performance implications of inter-group structures in interorganizational NPD projects. The results point to distinct ways in which the same inter-group structure could differentially or similarly impact project performance and buyer learning in NPD projects. For instance, co-location helps with both project performance and buyer learning in China, which shows the possibility of simultaneously improving both aspects of performance. In contrast, formalization helps with project performance in the US while hurting buyer learning in China, which shows a trade-off relationship between the two types of performance. For buyer learning, we witness a stronger contingent role played by the country context. In contrast, the effect of inter-group structure on project performance is more universal and less country-dependent. These results suggest the importance of simultaneously considering multiple types of performance when studying project structures in interorganizational innovation.

Our results show support to the relevancy of an organizational dependence view for differentiating performance implications of various inter-group structural dimensions in interorganizational project teams. By reducing uncertainty emanating from dependence asymmetry, formalization helps in creating an efficient NPD process in both countries. By increasing joint dependence, task interdependence facilitates buyer learning and co-location increases project performance in both countries. Overall, our results suggest that project success relies on a higher level of joint dependence with a prudent context-specific management of dependence asymmetry. These results lay a foundation for future studies that adopt an organizational dependence view to study effects of joint dependence and dependence asymmetry in interoganizational collaboration.

Unlike the other three dimensions, task interdependence relates to the value gained by performing two tasks together as compared to the value received when they are done independently. Previous literature has argued that task interdependence enhances cooperation by intensifying interactions and increasing perceived mutual dependence. With high task interdependence, individuals perceive others as closely-coupled partners rather than independent or competing entities. Such perceived mutual dependence encourages the emergence of collaborative behaviors and norms, such as open communication, autonomous adaptation, mutual respect, trust, and reciprocity. Our results confirm these findings and further show that one benefit of task interdependence is enhanced buyer learning. We also found that an interdependent task structure does not necessarily mean a less efficient and effective process, given the insignificant effects of task interdependence on project performance. Overall, our results suggest a more positive view about structuring a task interdependent structure to organize multi-group project teams.

Managerial Insights

This study helps project managers understand how inter-group structural factors distinctively influence NPD project outcomes. Specifically, we show that formalized rules and procedures improve project performance. However, managers need to recognize the adverse impact of formalization on buyer learning in certain national contexts. Hence, a balanced approach that incorporates some degree of informality in project management should work best for improving multiple goals simultaneously. Managers need to formalize inter-group interactions by specifying roles and rules, while leaving enough room for members to explore innovative ideas.

In NPD projects, managers often rely on an interdependent task structure with the hope that it fosters learning and instill a sense of team spirit. Our study supports the use of interdependent task structure in NPD projects. It enables utilizing complementary capabilities of the supplier. By jointly performing a task with the supplier, the buyer learns new innovation possibilities that could be part of subsequent NPD projects. The negative effect of task interdependence on project performance was not confirmed in our study, which further supports the benefits of an interdependent task structure. Buyer and supplier members can be co-located and be guided by formal rules and procedures when working in an interdependent task structure. In certain national contexts, spatial proximity not only enhances efficiency but also creates opportunities for buyer learning. Our findings show that centralized structures are detrimental in NPD projects for either project performance or buyer learning, depending on the underlying cultural, social and institutional contexts. So managers need to be cautioned when relying on a hierarchical administrative structure to manage an interorganizational NPD team.

Results of this study point to the importance of considering the national context, as a contingency factor, when organizing an interorganizational team. Our focus on the US and China is relevant in providing important insights to practicing managers since these two countries play important roles in emerging global product development initiatives. The findings from our study have direct implications for project managers in charge of interorganizational NPD teams in these two countries. Our results also present some directions for managers engaged in interorganizational NPD projects conducted in other countries to structure NPD teams to better fit the underlying cultural contexts.

Source: Yan, T., Nair, A. 2016. Structuring supplier involvement in new product development: A China-US study. Decision Sciences, 47(4), 589-627.

Continuum of Measurement Scales in Just-In-Time (JIT) Research

In a recently published study, my co-authors and I compare the predictive validity of single-item and multiple-item measures utilized in Just-in-Time (JIT) research. The study examines if single-item measures could be used for some of the JIT practices, especially if the object of inquiry is concrete singular and if the attribute to be researched is concrete. Arguments are developed for the concrete nature of the JIT practice of “set-up time reduction” and we examine the ability of a single-item measure of this variable to predict the criterion variable (delivery performance). In addition, the study also examines the efficacy of using multiple-item measures for variables that are abstract in nature, and thereby attempts to develop a continuum of JIT constructs ranging from concrete to abstract. The results obtained by analyzing two sets of survey data show that multiple-item measures are not necessarily more valid than single-item measures for all constructs. The findings provide evidence that multiple-item measures and single-item measures for scale development should be contingent upon the nature of constructs. For concrete constructs, single-item measures are as valid as multi-item measures. Meanwhile, for abstract constructs it is important to ensure that multiple items are considered to capture the multi-dimensional nature of these constructs. Results also reveal that JIT practices display significant differences in terms of abstract/concrete perceptions. The paper presents theoretical and practical implications of the findings, and offers directions for future research.

Data was collected by means of a survey administered to part-time MBA students of a large public university located in U.S. The students work in a wide range of industries including banking, manufacturing, IT, and healthcare. Since JIT practices are applicable in both manufacturing and service industries, two versions of the questionnaire were administered; one for respondents with experience in manufacturing sector and the other for respondents with experience in the services sector. The survey respondents represent very large organizations with, on average, more than 10,000 employees in both the manufacturing and service organizations. Respondents from manufacturing organizations reported that, on average, there were 923.82 people in their department. Respondents from service organizations reported that, on average, there were 506.10 in their department. The respondents represent several diverse industries including automotive, oil, telecommunications, food manufacturing, chemicals, healthcare and pharmaceuticals in the manufacturing group, and banking, financial services and software in the service group.

The respondents work at the positions such as project manager, quality engineer, controller, analyst, operations manager, vice president, senior consultant, and business specialist. The tenure of the respondents with their current employers range from 6 months to 20 years with an average of 5.23 years for the manufacturing group, while this time range from 1.5 months to 34 years with an average of 4.86 years. These figures indicate that the respondents spent sufficient time at their positions to be able to comment on the JIT related processes and practices. The survey items were adapted from previous research. The respondents were asked to rate the extent to which they used various JIT practices. A seven-point Likert scale where 1 indicates strong disagreement and 7 indicates strong agreement was used. A ‘not applicable’ (N/A) option was provided, as well as performance measures. We received 260 responses during this first round of data collection. In line with literature, the constructs considered in hypotheses 1 to 3 are operationalized as follows:

Single-item conceptualization of set-up time reduction (STR(1)):

Manufacturing industry: We have low set-up times of equipment in our plant.

Service industry: We have low setup times of equipment in our service processes. 

Multiple-item conceptualization of set-up time reduction (STR(4)): 4 item scale

Manufacturing industry: 1. We are aggressively working to lower set-up times in our plant; 2. We have converted most of the set-up times to external times while the machine is running; 3. We have low set-up times of equipment in our plant; 4. Our crews practice set-ups to reduce the time required.

Service industry: 1. We are aggressively working to lower setup times in our service processes; 2. We have converted most of the setup times to external times such that the setups can be performed while the service is being offered; 3. We have low setup times of equipment in our service processes; 4. Our crews practice setups to reduce the time required.

Single-item conceptualization of delivery performance (DP(1)):

Manufacturing and service industries: How does your organization rank relative to your competitors in terms of the delivery performance?

Multiple-item conceptualization of delivery performance (DP(3)): 3-item scale

Manufacturing and service industries: 1, How does your organization rank relative to your competitors in terms of the delivery performance?; 2. How does your organization rank relative to your competitors in terms of fast delivery?; 3. How does your organization rank relative to your competitors in terms of lead time (order to delivery)?

A second wave of data was collected to test Hypothesis 4. An online survey was sent to 2500 practitioners to measure perceived concreteness and abstractness of JIT constructs.

Specifically, in the survey we first provide the definitions of “concrete” and “abstract” constructs as follows:

Concrete: A JIT practice is "concrete" if a single item/question is sufficient to capture its core underlying essence. There is very high level of agreement as to what the practice refers to.

Abstract: A JIT practice is "abstract" if multiple items/questions are needed to capture its core underlying essence. The practice has several dimensions or characteristics.

Then the respondents rate the JIT practices within a continuum with “Definitely Concrete” and “Definitely Abstract” representing the two ends of the continuum. We received 310 complete responses. These respondents represent a wide variety of titles ranging from Master Production Scheduler to Vice President of Operations. All respondents have at the least an undergraduate degree in business and an average work experience of 21 years providing reasonable evidence that the respondents are aware of the practices underlying the JIT domain. For both waves of surveys we conduct several t-tests to test for non-response bias. We assume that the responses of the later waves of respondents are representative of the non-respondents. The early wave and the late wave respondents were compared using “Tenure with the company” for manufacturing and service groups to test whether non-response was a problem in the sample. As a result, we did not observe any significant differences between the waves of responses. 

As an outcome of the study we present the following continuum of scales that ranges from highly concrete to highly abstract:

STR: Set-up time reduction	RMS: Repetitive master schedule
SLS: Small lot sizes	PM: Preventive maintenance
JIT: JIT delivery from suppliers	EL: Equipment layout
SQL: Supplier quality level	PDS: Product design simplicity
MFW: Multifunction workers	KANBAN: Kanban
SGPS: Small-group problem solving	PSS: Pull system
TRA: Training	MRP: MRP adaptation to JIT
DSA: Daily Schedule adherence	ACC: Accounting adaptation

Source: Nair, A., Ataseven, C., Habermann, M., Dreyfus, D. 2016 Toward a Continuum of Measurement Scales in Just-In-Time (JIT) Research – An Examination of the Predictive Validity of Single-Item and Multiple-Item Measures. Operations Management Research, 9(1-2), pp.35-48.

The roles of product complexity and managerial behavior on product design decisions

In a recently published article my co-author and I show that the choice of the level of centralization of product design decisions should be made contingent to the product complexity and behavioural factors of project managers involved in the decisions. In particular, we examine the influence of the cognitive ability, resistance to change, and cognitive effort of the project managers on the choice of the level of centralization of product design decisions. A methodology coming from complexity science is adopted and a simulation analysis is carried out. Results confirm that product complexity affects the relationship between the level of centralization of the product design decisions and product performance. Furthermore, we show that the benefit of centralized product design decisions are influenced by the level of cognitive effort, cognitive ability, and resistance to change of project managers. The analysis is performed in two different contexts characterized by varying levels of trust between the buyer and supplier. 

These findings provide interesting managerial implications. We prescribe project managers involved in new product design first clearly identify the level of trust charactering the buyer-supplier relationship. When there is high trust between the buyer and supplier, the produce complexity is low, and the cognitive load placed on the project managers is low, we prescribe that the buyer should adopt a highly centralized new product development process. We find this to be the case independent of the cognitive ability and resistance to change of decision makers. For high product complexity, independent of the cognitive effort, centralized product design is highly recommended when the project managers possess high cognitive ability. In the other cases, we find that centralization does not deliver much benefits. In these other cases, low centralized product design decisions could also help in obtaining the desired product performance.

On the other hand, when there is low trust between buyer and supplier, the decision maker has low cognitive ability, and the problem complexity is also low, high centralization is beneficial for improving product performance. High level of centralization is also beneficial when the product complexity is high and the cognitive ability is high. These results hold independent of cognitive effort and resistance to change of decision makers. In all other circumstances, low centralization is prescribed.

Source: Giannoccaro, I., Nair, A. 2016. Examining the roles of product complexity and managerial behavior on product design decisions: An agent-based study using NK simulation. IEEE Transactions on Engineering Management, 63(2), 237 – 247.

Efficiencies in translating R&D and Advertising Investments into Sales and Customer Satisfaction

In a study I examined the efficiencies of nine leading consumer durable manufacturing firms in translating their investments in R&D and advertising into sales and customer satisfaction. Four firms - Ford, GM, Honda, and Toyota – represent leading automobile manufacturers. The remaining five firms - Apple, Dell, Hewlett-Packard, Maytag, and Whirlpool – represent consumer electronics, computer hardware and major appliances. The research model is as follows.

Figure 1:

Longitudinal five-year secondary data (1999-2003) was secured for the firms considered in this study. Using Data Envelopment Analysis (DEA) approach, this study evaluated the efficiency scores, peer groups and slacks in inputs and outputs of the sample firms.The sample firms and their data characteristics for 1999-2003 are summarized in table 1 below.

Table 1:

NAME	Mean R&D Investments[1] (1998-2002)	Mean advertising investments (1999-2003)	Mean CSI (1999-2003)	Mean Net Sales (1999 – 2003) (in millions $)
APPLE COMPUTER INC	375	230	74.00	6,285.80
DELL INC	307	348	77.60	33,033.80
FORD MOTOR CO	6,800	2,880	80.67	164,363.20
GENERAL MOTORS CORP (GM)	5,790	3,986	81.60	179,364.60
HEWLETT-PACKARD CO (HP)	2,718	1,340	70.90	53,205.40
HONDA MOTORS LTD.	3,045	1,852	82.40	62,071.40
MAYTAG CORP	80	163	83.60	4,470.60
TOYOTA MOTOR CORP	4,424	2,664	83.20	113,585.20
WHIRLPOOL CORP	237	176	83.60	10,874.20

[1] I consider a one-year lagged effect of R&D investments as input. Thus, R&D investments are considered for the time-period 1998-2002.

Panel data analysis was conducted by using the window analysis and Malmquist index approaches in DEA. The efficiency changes of each firm over the course of five years were examined and the efficiencies of firms relative to others in the sample were investigated. 

The efficiency of each firm changes over the time duration of study. It would thus be interesting to understand the pattern of these changes for the sample firms. The trend in efficiency patterns of the automobile manufacturers is presented in figure 2 and the trend in efficiency patterns of the consumer electronics and major appliances manufacturers is presented in figure 3.

Figure 2:

From figure 2 we observe that the two major U.S. automobile manufacturers – Ford and GM – follow similar trend. The efficiency score for these two firms decrease during 2001.

Figure 3:

 

The patterns presented in figure 3 suggest that all the units in the sample of consumer electronics and major appliances manufacturers experienced a decrease in efficiency during 2001. Dell, Maytag and Whirlpool follow quite similar pattern. The efficiency scores of Apple Computers were observed to be lower than the other sample units during all periods of this study.

The patterns of technical efficiency and technical change of the automobile manufacturing firms and consumer electronics and major appliances manufacturing firms are presented in figures 4 and 5 respectively.

Figure 4:

Figure 5:

The following frequencies of efficient firms in peer group for automobile manufacturing firms were observed:

Toyota (2003): 14

GM (2000): 13          

Honda (1999): 5

Honda (2001): 5

As can be observed, Toyota Motor Company in 2003 provides directions for good practice. For consumer electronics and major appliance manufacturing firms the following frequencies were observed:

Whirlpool (2000): 10

Maytag (2000): 6

Dell (2003): 6

Dell (2000): 3

HP (2003): 4

Whirlpool (1999): 3

From the above frequency counts it can be noted that Whirlpool 2000 provides evidence of good practice.

An explanation for the drop of efficiency in 2001

The drop in efficiency during 2001 can be explained by the downturn experienced by the world economy in that year. The growth rate in world GDP fell from 4.7% in 2000 to 1.9% in 2001 (Prometeia, Forecast Report, December, 2001). The US GDP dropped from 4.1% in 2000 to 1.1% in 2001

Source: Nair, A. 2005. Examining the efficiencies in translating R&D and Advertising Investments into Sales and Customer Satisfaction: A Longitudinal Study of Consumer Durable Goods Manufacturing Firms Using Data Envelopment Analysis. Unpublished manuscript.

Entrepreneurial Orientation and Firm Performance

In a study my co-authors and I propose a structure of corporate entrepreneurship in manufacturing firms, and links it to manufacturing strategy. The study also highlights the role played by product-process dynamism and competitive priorities. In order to empirically evaluate these relationships, data was collected from 66 manufacturing firms and analyzed. The results show that firms can attain higher entrepreneurial orientation by co-aligning risk taking, innovation, and proactiveness, and achieve better performance by doing so. Such firms also tend to operate in highly competitive environments, and configure product lines and internal processes accordingly to quickly adapt to changes. Finally, entrepreneurial firms tend to compete on the dimensions of high performance design, quality, and on-time delivery. Overall, the findings establish corporate entrepreneurship as a performance enhancing strategy, and provide insights into the constituent elements of entrepreneurial orientation in a manufacturing context. Implications of our study for research and practice are also discussed. The following research questions are addressed in this study:

• What is the structure of entrepreneurial orientation in manufacturing firms?
• Do manufacturing firms with higher entrepreneurial orientation also exhibit higher performance?
• How does competitive intensity differ among firms with varying levels of entrepreneurial orientation?
• Do firms with varying entrepreneurial orientation place different level of emphasis on product-process dynamism and competitive priorities?

The research model is as follows:

The results obtained from an analysis of survey data show that entrepreneurial orientation is positively associated with firm performance after controlling for sales, process type, and fulfillment strategy. Further, the findings suggest that manufacturing firms with higher entrepreneurial orientation operate in highly competitive business environment. These firms frequently change their product lines and manufacturing processes. Firms with high entrepreneurial orientation compete in the marketplace based on high performance design, consistent quality, and on time delivery. This result is quite consistent with the notion of how proactive enterprises and innovator firms compete.

The results of this study highlight the importance of innovation in manufacturing firms. Firms with higher entrepreneurial orientation tend to focus on the competitive priority of high performance design. By focusing on high performance design, entrepreneurial firms take these periods into their stride and redefine the competitive landscape. For these entrepreneurial firms, technological change, defined as radical or incremental innovations, plays an important role in the formation of new markets and in the development of new products and processes as a part of the operations strategy. This study brings innovation, manifested in terms of high performance product design, to the forefront in manufacturing firms. Since entrepreneurial orientation is positively associated with high performance and entrepreneurial firms give high level of priority to high performance design, it behooves research and practice to give due consideration to this important variable in manufacturing strategy.

Our study emphasizes a distinct view of dynamism in products and processes. Specifically, the results of this study highlight that entrepreneurial firms distinguish themselves from others in terms of their ability to frequently change product lines and manufacturing processes. This could partly be due to the increasingly competitive and dynamic environment faced by these firms. However, it could also be part of a conscious and proactive approach towards staying ahead of competition by taking calculated risks. This perspective of product-process dynamism puts manufacturing strategy at par with marketing strategies in a firm’s attempt to gain competitive advantage. More research can shed light on this important variable, and a deeper understanding would enable the formulation of a proactive manufacturing strategy in practice.

Overall, the findings of this study suggest that entrepreneurial firms pursue high performance design approach, which involves not only transforming the product performance frontier, but also reliably delivering such products to the marketplace in a time effective fashion. Further, such firms tend to operate in a relatively more competitive environment and configure manufacturing process that can quickly adapt to changing market conditions. The configuration of expertise and routines is subject to managerial decision-making. Thus, managers have a choice about pursuing a viable entrepreneurial configuration. This study informs the managers on how to configure processes and routines to achieve high entrepreneurial orientation and under what conditions entrepreneurial orientation based strategy makes more sense. The results of the study provide directions to reverse the current erosion of manufacturing in US. The typology presented in this paper provides a firm an understanding of its entrepreneurial orientation, how it can successfully adopt such an orientation, and conditions under which such an orientation will result in a high payoff.

Source: Malhotra, M.K., Saeed, K.A., Nair, A. 2009. Entrepreneurial Orientation and Firm Performance: An Empirical Examination of Manufacturing Strategy Typology based on Corporate Entrepreneurship. Unpublished manuscript.

Project Structure and Buyer-supplier Collaboration Quality in New Product Development: A US-China Comparative Study

In a study my co-author and I study how the national context (the social system) interacts with the project structure (the technical system) in influencing buyer-supplier collaboration quality, an indicator of project-level effectiveness of inter-firm interactions. We further examined how structural deviation, the difference between the actual and ideal project structure, differentially influence collaboration quality in China and U.S. We tested the hypotheses using survey responses from 214 U.S. based and 212 China based buying companies. Due to their distinctive national cultures and economic ideologies, the two countries differ in their ideal project structures, the ones that lead to the highest level of collaboration quality. Our research model is as follows:

 

Results suggest that a formal project structure is only effective in enhancing buyer-supplier collaboration quality in the U.S. and not in China. Centralization hurts collaboration quality only in U.S. based projects. These results highlight the important and differential role played by the administrative structure for motivating collaborative behaviors in different national contexts. The task structure, characterized as task interdependence, does not play such a differentiating role as the results show it to be equally effective in improving buyer-supplier collaboration quality in both U.S. and Chinese NPD projects. Supporting the STS view, we also show that the ideal project structure, a result of the interaction between the social and technical systems, varies between U.S. and China. Specifically, the ideal project structure in U.S. is more formal and less centralized as compared to that in China. We also found some support for our prediction that the negative effect of structural deviation on collaboration quality is dampened by China’s national context. Below we discuss theoretical and managerial implications of these findings.

This study presents key insights for project managers about the relative importance of different aspects of the project structure in influencing the quality of buyer-supplier interactions. Compared to the task structure, the administrative structure has a more nationally-contingent impact in shaping buyer-supplier project interactions. Specifically, a formal and decentralized structure, though usually advocated by the project management literature, does not always lead to more effective project-level interactions, especially in countries with similar cultural and economic contexts as China. The significant association between task structure and collaboration quality in both countries suggests the importance of assigning interdependent tasks to each group for encouraging collaborative behaviors. This finding questions the traditional wisdom about outsourcing modular, rather than integral, tasks to external suppliers with the purpose of reducing transaction cost. Specifically, we show that task modularity, though reducing short-term transaction costs, might hurts the quality of inter-firm interactions, which limiting the dyad’s value creation potential. Overall, our findings suggest that project managers could encourage effective project-level collaborations by creating mutually dependent tasks involving both buyer and supplier sub-groups.

Results from this study point to the importance of considering the national context when structuring an interorganizational team. Testing the conceptual model in two culturally distinct countries, China and the U.S., reveals varying effects of project structures on collaboration quality. The comparison between U.S. and China presents two culturally distinct nations who are playing important role in the emerging global product development initiatives. While U.S. has always been a leader in NPD, China is increasingly displaying its product development capabilities. The findings from this study have direct implications for project managers who are in charge of NPD teams in these two countries. Specifically, a formal and decentralized inter-group structure is found to be more effective in enhancing collaboration quality in the U.S. than in China, while task interdependence is equally effective in promoting inter-group collaboration in China and in the U.S. Thus, when initiating interorganizational product development efforts in the global context, project managers are advised to consider the impact of the national culture and economic ideology of different locations in order to cultivate a high-quality collaboration process. By revealing country-level contingency effects evidenced in Chinese and the U.S. based NPD projects, this study shows the inappropriateness of a “one-size-fits-all” approach when structuring NPD teams globally.

The stronger negative effect of structural deviation in the U.S., as compared to China, also has managerial implications. In low-context cultures, such as the U.S., project manages need to pay more attention to identify and stick to the ideal project structure because deviating from it adversely impacts collaboration quality. As shown in this study, the ideal project structure should be congruent with social values held by project members. Such structure-value congruence motivates collaborative behaviors among project members. In contrast, managerial efforts of ensuring maximum conformance to the ideal project structure are less rewarding in high-context cultures, such as China, where negative effect of divergence from the ideal-state is partly mitigated by cultural ethos that dominate public life beyond NPD projects. In such high-context cultures, rather than solely relying on the governance of the ideal project structure, project managers need to understand the implicit rules and unspoken protocols embedded within the cultural ethos in order to cultivate a high-quality collaboration process.

Source: Yan, T. and Nair, A. 2015. Project Structure and Buyer-supplier Collaboration Quality in New Product Development: A US-China Comparative Study. Unpublished manuscript.

Buyer-supplier network structure and product architecture

In a study my co-authors and I investigate the contingent role of product architecture on the relationship between buyer-supplier network structure and product quality. The hypotheses are tested on a combination of primary and secondary data from the North American automobile industry. The results suggest that correspondence between buyer-supplier networks and product architecture networks may not be conducive for product quality. While buyer network density (or tight coupling) is better suited for improving the product quality of modular systems, buyer network centrality (or loose coupling) is better suited for improving the product quality of integral systems. The implication is that greater information sharing between buyers and suppliers is more likely to improve product performance of modular products as compared to integral products.

To test our hypotheses, we assembled data using a combination of archival and primary sources. We focus on firm-system as the unit of analysis. This choice was guided by the observation that there is considerable variation in the composition of supplier networks for different systems of a given firm. We collected data on buyer-supplier links for twelve vehicle systems in 2010. The systems we examine are as follows: transmission, major engine system, engine cooling, suspension, drive systems, exhaust, electrical, power equipment, body hardware, braking system, climate system and fuel system. We focus on these 12 vehicle systems instead of more disaggregate subsystems or vehicle components to keep the functional interactions or dependencies tractable (Novak and Eppinger 2001, Gokpinar et al. 2010). Additionally, a practical consideration was that data on product quality are available at the vehicle system level but not at the subsystem level. We identify suppliers of thirteen automobile manufacturers with significant operations in North America (BMW, Chrysler, Ford, General Motors, Honda, Hyundai, Kia, Mazda, Mercedes-Benz, Mitsubishi, Nissan, Subaru and Toyota). The thirteen auto manufacturers accounted for approximately 85 percent of vehicles sold in North America. The data collection efforts yielded a total of 964 unique suppliers for 13 automobile firms and 12,667 unique B-S relationships. The following figure presents an illustrative supply network for the electrical system network comprising of 3,656 ties between 507 entities (13 automakers and 494 suppliers).

 

The data on quality of auto manufacturer’s vehicle systems for 2011 was assembled from Consumer Reports. There are two important issues to be considered in matching B-S relationships with quality outcomes. First, data on B-S relationships was available at the ‘automaker-vehicle system’ level whereas data on product quality is at the ‘model-vehicle system’ level. For example, consider the case of Subaru of America, the automaker. While we constructed the supplier network for Subaru, the quality data is available at the model level (e.g., Outback, Legacy) of Subaru. We aggregated model-level quality by weighting on model sales to construct the automaker’s quality for a vehicle system. Second, we only included suppliers of models that were manufactured in North America. For example, Subaru of America manufactured three of its five models (i.e., Outback, Legacy and Tribeca) in its North American assembly plants. We identified suppliers of these three models of Subaru and excluded suppliers of two manufactured outside North America. Likewise, we aggregated product quality for Subaru by using sales weights for the three models manufactured in North America.

We relied on primary data sources to operationalize the Strength of Design Interface (SDI) variable. We conducted 31 in-depth interviews with product and design engineers in automobile and supplier firms to gauge the dependencies between various systems in a vehicle. The in-depth interviews lasted approximately 90 minutes in duration. The experts participating in the survey were employed at General Motors (USA and India), Ford, Chrysler, Honda, Toyota, BMW, Porsche, Hyundai (USA and South Korea), Aisin (USA), Bosch (USA and South Korea), Cummins, Denso, Mando, SAIC Motors, Maruti (India) and Ashok Leyland (India) and had, on average, approximately 13 years of experience in automotive design. To assess SDI, we asked product and design engineers to evaluate the degree of information, spatial, structural, material and energy dependencies between vehicle systems (see ‘Measures Section’ for details on the questionnaire items). We also asked these experts whether the level of dependency criticality and absolute criticality of systems vary across major automakers. All but one expert indicated that dependencies do not vary across automakers. In other words, the strength of the design interface is system-specific and is not contingent on the automobile manufacturer.

We also collected data on several supplier and buyer characteristics. Data on the size of the supplier’s plants (in square feet), distance in miles between the supplier and auto manufacturer, the union status of suppliers, and quality awards of supplier were obtained from ELM Analytics. We also collected data on buyer characteristics such as sales from the Ward’s Automotive Yearbook and R&D expenditures from COMPUSTAT and annual company reports.

A test of our hypotheses requires a close alignment between the theory, measures and the empirical model. We model the impact of buyer-supplier network characteristics in time period ‘t-1’ on product quality in time period ‘t’. The temporal separation facilitates a more confident interpretation of the quality consequences of B-S network structure. Our final dataset for empirical analyses is comprised of 156 firm-system observations (13 makes x 12 systems). The B-S network characteristics and control variables are for 2010 and product quality data is for 2011.

Our findings show that buyers in dense networks experience better product quality outcomes compared to buyers that are centrally located. We find that integral systems have higher quality compared to modular systems. More importantly, our results reveal that buyer network density enhances the quality of modular systems to a greater extent compared to integral systems. On the other hand, a central position for buyers is beneficial for improving product quality for integral systems than for modular systems. 

The findings of this study offer numerous valuable insights for managerial practice. In recent years, there has been increased emphasis on improving supply chain performance. The emphasis has been on using concepts such as modularization, flexible and lean manufacturing to boost performance. Despite such advances, the poor performance of supply chains, as evidenced in growing number of product recalls in the marketplace, continues to frustrate and disenchant managers. Our findings caution managers to refrain from viewing network density as beneficial and network centrality as detrimental to quality. Our findings, instead, point to the need to evaluate the normative B-S network structure in conjunction with the architecture of the product. We performed a univariate transfer function analysis to understand the economic value added by matching buyer-supplier network structure and product architecture. We computed the direct impact of changes in automakers’ network density and network centrality on product quality for high and low levels of SDI. The high and low levels for buyer network density, buyer network centrality and SDI are set at the 90th and 10th percentiles. To compute the dollar impact of change in product quality, we turn to previous research that has assessed the shareholder value impact of product quality. Tellis and Johnson (2007) note that increasing product quality from 10^th percentile to 90^th percentile value leads to a 9.35% increase in shareholder wealth. The average market capitalization of publicly traded automobile firms in our sample is $73.37 billion. In our sample, this translates to an increase of $6.86 billion. The difference in product quality between 90^th and 10^th percentile in our sample is 1.87 points. Thus, a one point increase in product quality corresponds to an increase in market capitalization of $3.67 billion.

Our post-hoc analyses reveal that if buyer network density is increased from the 10^th percentile to the 90^th percentile, there is significant increase in product quality for low SDI systems relative to high SDI systems (difference in quality = 0.11 points). That is, when buyer network density is increased, there is a greater increase in product quality for modular systems than for integral systems. The total economic value created when buyer network density is aligned with modular systems is $403.56 million. Although dense networks are costly to maintain because of intensive information sharing, our post-hoc analyses reveal that buyers could harness considerable economic value from dense ties by aligning it with the appropriate product architecture. Similarly, if buyer network centrality is increased from the 10^th percentile to the 90^th percentile, there is significantly greater increase in product quality for high SDI (system design interface) systems relative to low SDI systems (diff = 0.05 point change). Correspondingly, there is greater increase in shareholder wealth at high levels of SDI than at low levels of SDI. The total economic value created when buyer network centrality is aligned with integral systems is $183.43 million.

Source: Kalaignanam, K., Kushwaha, T. and Nair, A., 2015, January. Buyer-supplier network structure and product architecture. In Academy of Management Proceedings (Vol. 2015, No. 1, p. 13626). Academy of Management.

Environmental Innovations in Supply Network

Firms and their supply chain partners increasingly confront environmental challenges ranging from water pollution to landfill waste to climate change. In addition, they are experiencing greater pressure from customers and regulatory bodies to make sustainable products in environmentally friendly ways. Environmental innovations – new or modified processes, practices, systems, and products that reduce or completely avoid harm to the natural environment – provide new avenues for addressing these challenges. Such innovations, however, require the efforts of many firms in the dynamic and interconnected world of supply chains. Therefore, it is important to understand how these environmental innovations originate in and diffuse throughout supply networks.

Using a complex adaptive systems (CAS) view, longitudinal case studies of Hyundai and Samsung SDI, and an abductive research approach, my co-authors and I developed a multilevel process model and a set of theoretical propositions about how environmental innovations emerge within dominant buying firms and spread throughout their supply networks over time. Our model and corresponding propositions address an environmental innovation’s firm-level origins rooted in sensing, intuiting, interpreting and structuring processes, and its network-level dynamics, which feature diffusing, amplifying, organizing and synchronizing processes. Consistent with a CAS view, our main insight is that the process of environmental innovation in supply networks is an emergent phenomenon. That is, once the dominant buying firm’s internal processes of emergence play out and its eco-innovation spreads to the broader supply network, the innovating firm loses its ability to fully control the innovation. Consequently, self-organization and decentralized coordination take over. The process model is presented in the figure below.

Our proposed model has important implications for theory and practice. A refined understanding of environmental innovations in supply networks sets the foundation for future theoretical work on supply network dynamics. Our process model and theoretical propositions provide insights into how environmental innovations originate and evolve in supply networks. The model lays the groundwork for examining innovation-oriented supply chain dynamics. By considering both firm and network level dynamics, our study presents implications for multi-level theorizing in the area of sustainable supply chain management. Following complex adaptive systems perspective, we emphasize the role of small perturbations in setting forth positive set of consequences in the supply chain. Instead of trying to develop an exact future state of capabilities in a firm or a supply network, our study presents directions for developing dynamic operational capabilities by focusing on behavioral patterns and routines. We promote the idea of achieving a balance between control and emergence while managing environmental innovations in supply networks. Our results suggest deliberate planning when environmental innovation process is still within the boundaries of the dominant firm, however, this should be followed by an indirect engagement with suppliers once the process unfolds in the larger network. We emphasize that the eight-phase pattern identified in the paper calls for a general mental model of the underlying complexity and dynamism within supply networks. In conclusion, our study offers practical guidance for organizations seeking to build sustainable supply chains and provides a foundation for future theoretical work in the area of environmental innovations.

Source: Nair, A., Yan, T., Ro, Y. K., Oke, A., Chiles, T. H., Lee, S-Y. 2016. “How Environmental Innovations Emerge and Proliferate in Supply Networks: A Complex Adaptive Systems Perspective.” Journal of Supply Chain Management, Volume 52, Issue 2, (Forthcoming).