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This study investigates supply chain management (SCM) practices in a specific fast fashion apparel (FFA) industry. The impacts of SCM practices on competitive advantage (CA) are investigated via mediating roles of supply chain agility (SCA) and partnership quality (PQ). Resource advantage (R-A) theory, in addition to resource-based view (RBV) and dynamic capability theories, is used as theoretical underpinning.

A mixed-method approach is adopted: a qualitative field study and survey research. Data from 296 apparel manufacturers in Bangladesh are analyzed using the partial least squares structural equation modeling (PLS-SEM) approach, involving reflective and formative, first- and second-order constructs and mediation tests using the Hayes PROCESS macro.

Both SCM practices and PQ significantly affect SCA. SCM practices are found to directly enhance CA, but, counterintuitively, only marginally. Only through mediations of SCA and PQ do SCM practices enhance CA significantly. This is a departure from past research that has postulated direct effects between SCM practices and CA.

This research is confined to the FFA industry and one national setting, Bangladesh. The data analyzed is also cross-sectional, with customary limitations on the temporal dimension.

SCM practices contribute to CA, but only through the mediation of PQ and SCA. This is an important directive to practitioners. Also, the second-order reflective measures for each construct indicate the specific SCM practices needed to maximize CA.

This study contributes to the literature on SCM practices in FFA industry, specifically the mediating roles of PQ and SCA, resulting in new, more nuanced findings that are important in dynamic business settings, driven by new theoretical perspectives incorporating R-A theory, which has hardly been utilized before in SCM research.

Longitudinal investigations are often suggested but rarely used in operations and supply chain management (OSCM), mainly due to the difficulty of obtaining data. There is a silver lining in the form of existing large-scale and planned repeated cross-sectional (RCS) data sets, an approach commonly used in sociology and political sciences. This study aims to review all relevant RCS surveys with a focus on OSCM, as well as data and methods to motivate longitudinal research and to study trends at the plant, industry and geographic levels.

A comparison of RCS, panel and hybrid surveys is presented. Existing RCS data sets in the OSCM discipline and their features are discussed. In total, 30 years of Global Manufacturing Research Group data are used to explore the applicability of analytical methods at the plant and aggregate level and in the form of multilevel modeling.

RCS analysis is a viable alternative to overcome the confines associated with panel data. The structure of the existing data sets restricts quantitative analysis due to survey and sampling issues. Opportunities surrounding RCS analysis are illustrated, and survey design recommendations are provided.

The longitudinal aspect of RCS surveys can answer new and untested research questions through repeated random sampling in focused topic areas. Planned RCS surveys can benefit from the provided recommendations.

RCS research designs are generally overlooked in OSCM. This study provides an analysis of RCS data sets and future survey recommendations.

The performance of cellular manufacturing (CM) systems has been rigorously investigated during the last two decades. The findings from these studies need to be systematically tabulated, given that they span a wide range of systems and experimental conditions. Some of the findings have also not been in agreement with the prescriptive literature on group technology (GT). No such survey of research exists to date. Attempts to fill the void by providing a taxonomy that categorizes these studies into simulation‐based, analytical and empirical studies. Also discusses past work in the context of various experimental factors and conditions, such as system configurations assumed, setup and operation times, scheduling rules, lot sizes and performance measures used. Summarizes major findings from each stream of literature from the point of view of both researchers and practitioners.

The purpose of this paper is to investigate two potentially key drivers of a firm's supply chain agility, namely strategic sourcing and firm's strategic flexibility. Despite some theoretical and conceptual works suggesting that some elements of these two constructs may relate to agility, this has not yet been assessed together empirically. This study aims to address this gap in the literature.

This study involves an empirical investigation of a theory‐based model based on the competence‐capability framework, and a dynamic capabilities theoretical perspective, where the internal competencies of strategic sourcing and firm's strategic flexibility relate to the dynamic capability of the firm's supply chain agility. This investigation also includes the testing of a possible mediation effect of firm's strategic flexibility on the relationship between strategic sourcing and the firm's supply chain agility. The model is tested utilizing data from 144 US manufacturing firms via partial least square methodology.

The results of the empirical study indicated that both strategic sourcing and firm's strategic flexibility were significantly related to the firm's supply chain agility. In addition, while a full mediation effect was not found on the part of strategic flexibility, there was evidence for partial mediation.

Given that the data are from specific US industries, the generalizability of current findings to other industries or countries may require additional investigation.

Given the attention paid to agility in terms of its importance to responding to business uncertainty, and more recently, as an important capability in managing supply chain disruption risks, this paper investigates how strategic sourcing and flexibility can contribute to agility.

The aim of this study is to investigate the relationships among strategic sourcing, e-procurement and firm performance, along with the moderating effects of business characteristics and environmental factors on these relationships.

This empirical investigation relies on structured survey responses from 137 managers of US manufacturing firms. The partial least squares-based structural equation modeling approach is used for data analysis.

The research results confirm that both strategic sourcing and e-procurement have a positive effect on firm performance. In addition, e-procurement is also found to have a positive impact on strategic sourcing. In addition, the research results suggest that business characteristics and the environment, especially the degree of competition, market turbulence, firm size and stage in product life cycle moderate these relationships significantly. The positive effects of strategic sourcing and e-procurement on firm performance are particularly enhanced under the right conditions.

This research is the first, to the best of our knowledge, to provide insights into the joint effects of strategic sourcing and e-procurement, and how business characteristics and the environment affect their roles on firm performance. In addition, firm performance is evaluated as a multi-dimensional construct involving financial, operational and supply chain aspects, with the measurements consisting of several second-order constructs. The study makes both theoretical and practical contributions.

The purpose of this paper is to apply expectancy theory to advance a conceptual framework which identifies factors that motivate and affect the adoption of supplier development (SD) activities.

The authors conduct a comprehensive literature review to identify salient contributions and conceptual gaps within prior SD studies. These conceptual gaps motivate the use of expectancy theory and the broader management literature to develop a conceptual framework of SD adoption.

The study results in the development of a two-stage conceptual framework in which two behavioral constructs – SD expectancy and valence – play an important role in mediating the effects of activity-, firm-, interfirm-, and environment-level factors on the adoption of SD activities. Accordingly, the authors advance 11 testable propositions that underlie the logical development of the framework.

The application of expectancy theory facilitates the integration of constructs culled from disparate theories into a cohesive conceptual framework. Highlighting the central role of motivational force, the conceptual development provides a behavioral explanation for the indirect effects of activity-, firm-, interfirm-, and environment-level factors on SD adoption.

The authors advance a set of factors associated with three successive stages of the SD planning process – partner selection, activity selection, and scope selection – that managers should consider when adopting a SD activity.

In contrast to prior research, which largely draws from economic or strategic theories, the authors employ a behavioral approach to advance a novel set of factors that influence SD adoption.

Over the past three decades, many researchers have studied the relationship between sales and production departments. This has raised the question: Does the quality of the relationship between production and sales affect the customer? This study uses survey methodology to examine the link between customer satisfaction and the interface variables (connectedness, conflict, coordination) from both a sales and a production perspective. Customer satisfaction responses are aggregated for each sales‐production combination and analyzed to determine the impact of the relationship between production and sales personnel. Product type (i.e. engineered‐to‐order (ETO)) is introduced as a moderating variable. Results indicate that there is a significant impact on customer satisfaction as a result of the cross‐functional situation when moderated by product type. The main managerial implication is that the internal relationship between sales and production is important to the customer, specifically in ETO product situations.

The purpose of this paper is, first, to utilize institutional theory to assess motivation for the adoption of Six Sigma. Second, to examine the role of an organization's innovation implementation climate and the fit between the innovation considered and the values of the organization's members on the implementation of Six Sigma. Third, to study the impact that the adoption and implementation of Six Sigma has on organizational performance.

Methods advocated in case study research were employed in the conduct of seven case studies. The research protocol consisted of identifying organizations in a variety of manufacturing industries, and conducting focused interviews with a minimum of three respondents in each company in order to improve validity.

This paper suggests that institutional theory proves to be an effective means by which to examine the adoption of Six Sigma. In addition, support for innovation implementation model suggested by Klein and Sorra is found. Each of the studied firms reported performance improvements as a result of the adoption and implementation of Six Sigma.

This paper contributes to a better understanding of Six Sigma adoption, implementation, and implementation effectiveness of Six Sigma by exploring how it is applied in different manufacturing contexts.

Justifying new manufacturing technology is usually very difficult since the most important benefits are often strategic and difficult to quantify. Traditional capital budgeting procedures that rely on return measures based on direct cost savings and incremental future cash flows do not normally capture the strategic benefits of higher quality, faster responses to wider ranges of customer needs, and the options for future growth made available by flexible manufacturing technology. Adding to these limitations is the difficulty of using traditional cost accounting systems to generate the information necessary for justifying new manufacturing investments. This paper reviews these problems and recommends procedures useful for assessing investments in flexible manufacturing technology.

The first objective of this paper is to identify the critical success factors (CSFs) and their corresponding key performance indicators (KPIs) for supplier development (SD) in a manufacturing environment. The second objective is to develop a methodology to analyze and evaluate the performance for SD using CSFs and their KPIs over the time.

In all, 13 CSFs and their corresponding KPIs for SD are established through an extensive literature review, discussion held with managers/engineers in different Indian manufacturing companies and conducting brainstorming sessions. A methodology is proposed using analytic hierarchy process (AHP) and performance value analysis to assess and evaluate the performance of SD over the time.

From an extensive analysis of the results, under the given circumstances, the growth of SD performance is positive at different progressive points along the time horizon.

This study has not been statistically validated in manufacturing supply chain for complete acceptability.

This study provides insights into the performance evaluation of SD using CSFs and their corresponding KPIs. The managers should capture their manufacturing environment which can reflect their own priority considerations to establish the impact of each KPI on its corresponding CSF.

Although many issues related to SD have been widely researched individually, few studies have been reported with a model to quantify, monitor, analyze, and evaluate the growth of SD performance in manufacturing environment in Indian context. The proposed model has the ability to capture the performance along KPIs and CSFs to draw fruitful conclusions regarding the success of the SD programme.