Search results

The primary purpose of this study is to investigate the strategic transition undertaken by e-retailers as they progress from meeting order-qualifier requirements to establishing order-winner elements within their operational frameworks. The overarching objective is to uncover how e-retailers can attain and sustain a competitive advantage in the marketplace.

This study adopted a focus group strategy, which involved collecting qualitative data. Evidence was collected from 41 customers and 16 business managers. The template analysis method was employed to code and organise themes identified during these discussions systematically.

The study identified 34 operational dimensions. 19 dimensions are related to e-retailing platforms and transaction processes, and 15 measurements are related to product or service characteristics. These dimensions were grouped into threshold resources, distinctive resources, threshold competencies and distinctive competencies. Distinctive resources and distinctive competencies are the most critical dimensions of e-retailing. These dimensions are subject to the “more is better” rule. Nevertheless, threshold resources are essential for e-retailing to be considered in the marketplace. It represents the “Must-be quality element.”

This study introduces the concept of a “cumulative model” in e-retailing. It offers strategic guidance for e-retailers seeking to navigate the complex landscape of competitive priorities. Companies can enhance their differentiation edge by identifying and emphasising distinctive resources and competencies. The study offers a nuanced understanding of the interplay between order-qualifier and order-winner elements in the pursuit of sustained competitiveness within the dynamic e-retail industry.

Social enterprises live in the limbo between social and market objectives, posing many operations management challenges. This study extends the discussion of operational priorities, which has focused on purely for-profit organisations, to the context of social enterprises by exploring, from a resource-based perspective, which resources and operational priorities are most important to them and how they are used to respond to conflicting demands.

Multiple case study research was carried out involving five Portuguese social enterprises, representative of the main sectors in which social enterprises operate in Europe. Ten semi-structured interviews with directors and other high-ranking respondents were conducted, and content was analysed to gather evidence on the key resources and operational priorities pursued by social enterprises. Cross-case conclusions were drawn, resulting in theoretical propositions and a conceptual framework.

Findings suggest that social enterprises rely on intangible resources and combine different operational priorities, which may vary throughout their lifecycle. Community engagement has emerged as a specific operational priority, in addition to those already reported in the manufacturing and services literature. To balance conflicting demands, most social enterprises studied combine innovation with community engagement or customer focus.

The study contributes to the development of knowledge about the operations strategy in the specific context of social enterprises, an organisational model that has not been systematically addressed in the operations management literature, and brings the discussion of operational priorities into the social enterprise field, thus strengthening the link between these two fields.

This study aims to explore the gaps concerning the organizational operant resources (OORs) of logistics service providers (LSPs) expected in outsourcing relationships. The study considers the views of both manufacturing firms (M-firms) and LSPs in India and DACH region (Germany, Austria and Switzerland) seeking gaps within and across regions.

This research employed a survey targeting executives from large M-firms and LSPs in both India and DACH. The perceptions about the importance and improvement expectations of 17 OORs are analyzed. A modified version of importance-improvement analysis (A-B), a novel comparative A-B analysis (CABA) method, has been proposed to identify the importance and improvement gaps in OORs between M-firms and LSPs within and across India and the DACH region.

There are more gaps between M-firms and LSPs in India compared to DACH. Cross-country comparisons reveal that LSPs in India and DACH have similar perceptions concerning the OORs, but M-firms in India have significantly higher improvement expectations than those in DACH.

This study proposes an analytical approach that enables managers to identify improvement areas and better align with their outsourcing relationship partners. It also highlights aspects that need to be considered while entering emerging markets such as India.

The analysis approach using CABA is novel. Also, among the cross-country studies, this is the first to compare outsourcing relationships in India with the DACH region while involving both users' and service providers' perspectives.

This research objective is to (1) examine the effect of organizational factors on quality performance, (2) examine the effect of quality performance on competitive advantage and (3) examine the mediating role of quality performance between organizational factors and competitive advantage.

The research sample includes 140 employees in the Windusari village-owned enterprise, in Magelang, Indonesia. Data are collected using 5-Likert scale questionnaires which follow Ferdousi et al. (2019). The dependent variable is a competitive advantage. The Independent variable is organizational factors which are top management support, employee empowerment, employee involvement, reward and recognition, training and customer focus. The mediating variable is quality performance. Data analysis uses path analysis provided by structural equation modeling.

Based on path analysis, organizational factors have a positive effect on quality performance, quality performance has a positive effect on competitive advantage and quality performance mediates the effect of organizational factors on competitive advantage. The results confirm the concept of quality management where continuous improvement of products and services can meet customer expectations and bring the organization to a better position in the industry to face other competitors.

This research extends the previous studies of the relationship between organizational factors and organizational outcomes by considering the effectiveness of the organizational process. This research also contributes to giving new evidence about the relationship between organizational factors, quality management and competitive advantage in the village-owned enterprise in Magelang, Indonesia. This research also contributes to updating the literature on the theory of quality management.

Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product and product–service innovation (PSI).

The ML approach is novel in the field of innovation antecedents at the country level. A sample of the Equatorian National Survey on Technology and Innovation, consisting of more than 6,000 firms, is used to rank the antecedents of innovation.

The analysis reveals that the antecedents of product and PSI are distinct, yet rooted in the principles of open innovation and competitive priorities.

The analysis is based on a sample of Equatorian firms with the objective of showing how ML techniques are suitable for testing the antecedents of innovation in any other context.

The novel ML approach, in contrast to traditional quantitative analysis of the topic, can consider the full set of antecedent interactions to each of the innovations analyzed.

Given the sudden increase in plant investments across the manufacturing sector due to recent disruptions in the global supply chain caused by the COVID pandemic, the Ukraine/Russian war, ocean piracy incidents, and others, there is a need to strategically align the investments decisions with the overall business strategy. This study aims to establish whether strategic alignment enhances the effect of plant investments on operational performance.

Using the fifth version of the Global Manufacturing Research Group (GMRG V) dataset, we employ a structural equation model (SEM) to establish the moderating role of strategic alignment in plant investments-operational performance relationships.

The results suggest that strategic alignment enhances the positive effect of plant investments on operational performance, especially in cost, delivery, flexibility, and innovation. However, we found partial support for the moderating role of strategic alignment on quality performance.

Although the study was based on the GMRG global dataset and numerous papers have been published using the same dataset, the use of a convenience sample on a select group of companies may limit the generalizability of the results. With the increase in new plant investments in computer chip manufacturing, electronics, and electrical in recent years, the findings could help corporate executives maximize the benefits of their investment decisions. Companies should ensure that their plant investment decisions are strategically aligned with their overall business strategy to achieve optimal outcomes.

With the increase in new plant investments in computer chip manufacturing, electronics, and electrical in recent years, the findings could help corporate executives maximize the benefits of their investment decisions. Companies should ensure that their plant investment decisions are strategically aligned with their overall business strategy to achieve optimal outcomes.

The study comprehensively demonstrates that the extent of improvement in operational performance depends on how closely plant investment decisions align with the overall company strategy. Manufacturers should align major investment decisions with competitive priorities driven by market requirements to enhance operational performance.

The ability of a business to outperform its rivals is known as its competitive edge, and it presents special difficulties in the context of the “digital revolution,” or the fourth industrial revolution. To obtain a competitive edge in the startup operations 4.0 era, this study aims to examine the organizational, technological and competence-related challenges presented by Industry 4.0. It does this by concentrating on the tools, competencies, methods, approaches, tools and strategies that are crucial. Using the Total Interpretive Structural Modeling (TISM) technique, the goal is to find, analyze and classify enablers for startup operations 4.0.

A closed-ended questionnaire and planned interviews were used in the data collection process. In startup operations 4.0, the cross-impact matrix multiplication applied to classification method is used to rank and categorize competitive advantage factors, whereas the TISM technique is used to analyze how components interact.

The study highlights the critical significance of the “Internet of Things (IoT),” “information technologies,” “technological platforms,” “employee empowerment,” “augmented reality (AR)” and “operational technologies” in its identification of 12 enablers for startup operations 4.0.

The main focus of the study is on the variables that affect startup operations 4.0’s competitive advantage.

Academics and important stakeholders can better understand the factors influencing competitive advantage in startup operations 4.0 with the help of this research.

Large businesses have been profoundly impacted by Industry 4.0 principles; however, startup operations 4.0’s competitive advantage has not received as much attention. This paper offers a fresh take on the concept of competitive advantage in startup operations 4.0 research.

Technology and market pressures are encouraging localized and small-series production in customer-driven industries. The purpose of this paper is to explore and understand the supply chain-, product- and process-design factors for small-series production in EU’s textile and apparel industry, to understand configuration decisions, priorities and challenges.

An interview study was undertaken with ten companies that represent diverse small-series production models and value chain roles. Interview data was analysed to identify supply network configuration characteristics, decision priorities and challenges.

Three small-series production models emerged from the analysis, differing with respect to adoption of process postponement and customization. The findings confirm and extend past research regarding diverse decision priorities and product, process, supply chain structure/relationship configurations. Challenges identified relate to planning (priorities) and implementation (configuration). Whereas competence availability and digital technology challenges are common, several difficulties are linked to production model like tensions related to priorities and small volumes, which are not found with customization.

Future research can make comparisons with other industry and location contexts; adopt dynamic approaches to distinguish between design and reconfiguration processes; and address indicated paradoxical-tensions.

The study findings can provide guidance for companies regarding identification of priorities and management of (planning/implementation) challenges impacting small-series production in T&A.

The paper brings a configuration perspective at the supply chain level to the problem of small-series production implementation, which demands holistic and context-specific understanding.

Customer experience management (CXM) and Innovation are two important capabilities on which businesses compete today. However, research to date has not empirically investigated their potential symbiotic relationship. Specifically, does better CXM improve innovation; similarly, does better innovation improve CXM? As a starting point, our research focuses on the former: how does effective CXM correlate with innovation success?

Data was collected by querying marketing managers from 251 goods and services firms involved in CX design and implementation. Managers answered questions related to their innovation efforts, customer experience management initiatives, and innovation outcomes. Cluster analysis was used to identify a taxonomy of CXM approaches contingent upon environmental factors (market turbulence, competitive intensity, and technological turbulence).

Our research found that higher levels of CXM engagement result in greater innovation success – i.e. higher success rates, revenues, and profits from new products or services. In addition, we find that there are three distinct approaches to CXM: (1) Extensive CXM approach (43% of firms in our sample); (2) Moderate CXM approach (39%); and (3) Limited CXM approach (18%). Firms with an extensive CXM approach operate in intensely competitive environments that are characterized by very high technological turbulence. Firms that employ a limited CXM approach operate in environments with the lowest levels of competitive intensity and technological change. Market turbulence did not factor into the choice of CXM approach.

To our knowledge, our study is the first to provide empirical evidence that firms adopt different CXM approaches. Further, we identify factors external to the firm that are considered when selecting these CXM approaches; namely, market turbulence, competitive intensity, and technological turbulence. Finally, our findings related to CXM approaches and innovation success indicate that managers should make investments in CXM to help improve innovation.

Effective green supply chain management (GSCM) has become a potentially valuable tool of securing competitive advantage and improving operational performance (OP) as competition is no longer exists between the firms but within green supply chains. The aim of this empirical study is to determine the link between GSCM practices (GSCMPs) and OP within the manufacturing sector of Bangladesh mediated by perceived competitive advantage (PCA). GSCMPs were divided into three further dimensions: green eco-design (GED), green supply chain partnering (GSCP) and internal green orientation (IGO).

The study selected 376 individuals as respondents who work as the top-level managers and the members of the Board of Directors at different Bangladeshi manufacturing firms through purposive sampling. A partial least square-based structural equation modeling (PLS-SEM) was utilized to identify the relationships between the three dimensions of, GSCMPs, and the single dependent variable, OP.

The study identified that two factors, GED and GSCP, have significant positive relationships with OP. On the other hand, another factor, IGO has a statistically insignificant relationship with OP. Regarding the mediating effects, the study identified that PCA can fully mediate the insignificant relationship between IGO and OP, and partially mediate the significant relationship between GSCP and OP. On the contrary, PCA has no mediating effect on the relationship between GED and OP.

This empirical study is an effort that examined the role of GSCMPs on the OP in the Bangladeshi manufacturing context. It is believed that this empirical investigation will prompt future theoretical studies and empirical experiments to enrich academia. Further, the findings of this study can serve as foundational guidance for policymakers and/or managers studying the formulation and implementation of GSCMP-related policies and strategies.