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In developing countries, construction organizations are seeking to effectively implement green innovation strategies. Thus, this study aims to assess the importance of green innovation practices and develop a measurement model for quantifying the green innovation degrees of construction firms.

A mixed-methods research approach is adopted. First, an extensive literature review is performed to identify potential green innovation items, which are then used to design a preliminary questionnaire. Next, expert interviews are conducted to pilot-test this questionnaire. Subsequently, by using a convenience non-probability sampling method, 88 valid responses are collected from construction firms in Vietnam. Then, one-sample and independent-samples t tests are employed to assess the importance of green innovation practices. Fuzzy synthetic evaluation (FSE) is also applied to quantitatively compare such practices. Finally, green innovation level (GIL) is proposed to measure the green innovation indexes and validated by a case study of seven construction firms.

This study identifies 13 green innovation variables, of which several key practices are highlighted for small/medium and large construction firms. The results of FSE analysis indicate that green process innovation is the most vital green category in construction firms, followed by green product and management innovations, respectively. As a quantitative measure, GIL could allow construction firms to frequently evaluate their green innovation indexes, thereby promoting green innovation practices comprehensively. Hence, construction firms would significantly enhance green competitive advantages and increasingly contribute to green and sustainable construction developments.

This research is one of the first attempts to integrate various green innovation practices into a comprehensive formulation. The established indexes offer detailed green innovation evaluations, which could be considered as valuable references for construction practitioners. Furthermore, a reliable and practical tool (i.e. GIL) is proposed to measure the GILs of construction firms in developing countries.

The development of green manufacturing has become essential to achieve sustainable development and modernize the nation’s manufacturing and production capacity without increasing nonrenewable resource consumption and pollution. This study investigates the effect of green industrial practices on technical efficiency for Thai manufacturers.

The study uses stochastic frontier analysis (SFA) to estimate the stochastic frontier production function (SFPF) and inefficiency effects model, as pioneered by Battese and Coelli (1995).

This study shows that, on average, Thai manufacturing firms have experienced declining returns-to-scale production and relatively low technical efficiency. However, it is estimated that Thai manufacturing firms with a green commitment obtained the highest technical efficiency, followed by those with green activity, green systems and green culture levels, compared to those without any commitment to green manufacturing practices. Finally, internationalization and skill development can significantly improve technical efficiency.

Green industry policy mixes will be vital for driving structural reforms toward a more environmentally friendly and sustainable economic system. Furthermore, circular economy processes can promote firms' production efficiency and resource use.

To the best of the authors' knowledge, this study is the first to investigate the effect of green industry practices on the technical efficiency of Thai manufacturing enterprises. This study also encompasses analyses of the roles of internationalization, innovation and skill development.

Trust is an important facilitator of successful B2B relationships. The purpose of this study is to investigate affect-based antecedents of both interpersonal and interorganizational trust, and their impact on the performance of buyer–supplier relationships. The authors ask two research questions: (1) What are affect-based dimensions of interpersonal and interorganizational trust? (2) How do interpersonal and interorganizational trust influence buyers’ operational performance?

The authors use data from an original survey of 156 buyer–supplier relationships between multinational enterprise subsidiaries and local suppliers in the Thai manufacturing sector to develop a structural model in which the authors test the hypotheses.

Consistent with social exchange theory and social psychology, the empirical analysis shows that affect-based dimensions at the individual level, namely, likeability, similarity and frequent social contact, and at the organizational level, namely, supplier firm willingness to customize and institutionalization of cooperation, are important for establishing trust. In addition, interpersonal trust enhances buyers’ operational performance indirectly via interorganizational trust.

Buying and selling firms may develop organizational trust by developing processes that enhance organizational trust. Individuals with purchasing or sales responsibilities may enhance trust in their personal relationship. However, such interpersonal trust needs to be translated to the organizational level to benefit organizational performance.

The findings contribute to the literature on affect-based antecedents and outcomes of trust. Specifically, the authors offer theory and empirical evidence regarding the contribution of salespersons toward affect-based dimensions of trust and its impact on buyer’s operational performance.

In the highly competitive business landscape, manufacturing firms need to adopt an effective manufacturing strategy to attain a successful world-class manufacturing status. Over the past few decades, the lean manufacturing (LM) approach has gained recognition as one of the foremost strategies for enhancing performance. However, the implementation of LM poses significant challenges due to several barriers. The purpose of this paper is to investigate the primary barriers to lean implementation within the apparel industry.

This paper used an exploratory study approach, using a three-part structured questionnaire to assess the level of agreement on different lean barriers. The measurement of these barriers was conducted using a five-point Likert scale. Empirical data were collected from 177 apparel companies located in Bangladesh.

The findings of the research highlight that the primary obstacles to implementing LI include a lack of understanding of the lean manufacturing system (LMS), the manufacturing process, the company culture and resistance from employees.

This paper could potentially limit the generalizability of this research, as it exclusively examines a single manufacturing sector – the apparel industry.

This paper will help practitioners in finding solutions to resolve discrepancies between current manufacturing practices and the LMS.

This paper fulfills an identified need to examine the extent of lean adoption within the apparel industry of Bangladesh.

This paper explores the role of Internet of things (IoT) enabling factors in adopting digital supply chain.

Analytical hierarchy process (AHP) was used to rank performance measures and prioritise the enabling factors. Semi-structured interviews were conducted to validate and support key research findings from the AHP analysis.

The results show that level of customer demand is the most important indicator in adopting IoT while the level of product/process flexibility is the least important. System integration and IoT infrastructure are the top two enabling factors in increasing the level of process stability, supply chain connectivity, and product/process flexibility, respectively. Furthermore, the study suggests that the enabling factors for IoT adoption are directly connected with organisational resources/technological capabilities that support the resource-based view theory. This research identified interdependencies between IoT enabling factors and key performance measures for IoT adoption success in managing the digital supply chain.

Supply chain managers can use the empirical findings of this study to prioritise IoT adoption, based on the relative importance of enabling factors and performance measures. The research findings are focused on broader supply chain practices of large companies rather than a specific industry and SMEs. Hence, any industry-specific adoption factors and SMEs were not evident from this study.

This research study empirically established priorities of enabling factors for IoT adoption, along with inter-dependencies among enabling factors as a basis for developing guidelines for IoT adoption.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Submission summary. This research paper aimed to investigate how work attitudes and behaviors differ across generations currently employed in Thailand's manufacturing and service sectors. The core results include that generational divides impact key structural relationships, while industry types showed no variations, and Generation X displayed higher work centrality, engagement, and effort than Generation Z. In response, managers are encouraged to tailor supportive strategies toward developing Generation Y’s leadership skills given their future leadership roles and stronger narcissism ties, as well as coaching Generation Z to optimize their engagement-effort connection as the newest labor market entrants.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The study proposes to determine the impending challenges to lean integration with Industry 4.0 (I4.0) in manufacturing that aims at achieving desired operational performance. Integrating lean and Industry 4.0 as the two industrial approaches is synergetic in providing operational benefits such as increasing flexibility, improving productivity, reducing cost, reducing delivery time, improving quality and value stream mapping (VSM). There is an urgent need to understand the integrated potential of OPEX strategies like lean manufacturing and also to determine the challenges for manufacturing SMEs and further suggest a strategic roadmap for the future.

The current work has used a combined approach on interpretative structural modeling (ISM) and fuzzy Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) approach to structure the multiple level analysis for the implementation challenges to integrate OPEX strategies with Industry 4.0.

The research has found that the indulgence of various implementation issues like lack of standardization, lack of vision and lack of trained support, all are the major challenges that inhibit the integration of OPEX strategies with I4.0 technologies in manufacturing.

The research has investigated the internal factors acting as a roadblock to lean and Industry 4.0 adoption. Further studies may consider external factors to lean and Industry 4.0 implementation. Also, further research may consider other operational excellence approaches and extend further to relevant sectors.

This study provides the analysis of barriers that is useful for the managers to take strategic actions for implementing OPEX strategies with I4.0 in smart manufacturing.

The research determines the adoption challenges towards the integrated framework. This is the first study to explore challenges in integrating OPEX strategies with I4.0 technologies in manufacturing SMEs.

Sustainability has become a priority for companies due to pressure from multiple stakeholders. In an overly competitive market, shareholders push for economic results, allowing lean manufacturing to establish itself as dominant paradigm in manufacturing. However, concerns grow regarding how lean implementation can allow companies to achieve sustainable development goals, or, if the resources required for a successful lean implementation can result in a detriment of environmental and social performance. This paper intends to help close the knowledge gap regarding the effects of lean manufacturing on sustainable performance from a triple bottom line perspective, and how operational, environmental and social outcomes interact between themselves.

Two models for the interaction between lean and sustainability were proposed. The first is called the “sand-cone” model, which poses that performance improvements derived from lean are cumulative on each one of the sustainability dimensions. The second is called the “trade-offs” approach. In this case, the resources required to improve one dimension of sustainability clash with those required by the others. Data were gathered from a sample of 133 Colombian metalworking companies and processed using structural equations models.

The results support the cumulative “sand-cone”, which follows a sequence of operational-environmental-social improvement in the presence of lean. For the “trade-offs” model, partial evidence suggests that they can occur in detriment of social performance.

The “sand-cone” and “trade-offs” are empirically tested for the first time in the context of sustainability, providing further knowledge into its interaction with lean manufacturing. The models’ results contribute to practitioners by providing a tested path for companies to improve their performance in a cumulative sequence that will provide better long-term results.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.

The tightening of environmental measures and policies in various countries around the world is forcing manufacturing companies, particularly those that make up the automotive industry, to improve their production processes, through the implementation of approaches such as lean production (LP) and Industry 4.0 (I4.0) technologies, to reduce industrial waste. However, the literature indicates that the implementation of LP and I4.0 does not always lead to an improvement in the level of operational performance (OP). Therefore, this study analyzes the effects of the implementation of LP practices and I4.0 on a green supply chain (GSC) and the operational performance of manufacturing companies in the Mexican automotive industry.

A theoretical research framework consisting of six hypotheses was developed and validated by applying partial least squares structural equation modeling (PLS-SEM) and using a sample of 460 companies from the Mexican automotive industry.

The results show that the level of OP of manufacturing companies increases substantially with the implementation of LP and I4.0 practices, as well as a GSC.

Managers of manufacturing companies will be able to use the results of this study to improve their production systems and to demonstrate the effects of these practices on OP.

This study contributes to the literature on LP and I4.0 by providing robust empirical evidence of the positive effects of implementing these approaches on the GSC and OP of manufacturing companies.