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Low‐stress mechanical properties of fabrics are very important in many applications as well as in manufacturing process control. Discusses the importance and potential applications of an on‐line mechanical property measurement system. In addition, the working principles of existing off‐ line fabric bending testers have been critically reviewed. It is suggested that the principle of a future on‐line system to evaluate fabric bending behaviour should be based on the characterisation of fabric loop shapes.

The purpose of this paper is to provide benefits for companies or organizations, which deal with fewer input-outputs and wanted to control their industrial processes remotely with a robust control strategy.

In this paper, an active disturbance rejection control (ADRC) strategy is used for the two tank level process plant and it is remotely monitored with the industrial internet of things technology. The disturbances in a primary and secondary loop of the cascade process, which are affecting the overall settling time (ts) of the process, are eliminated by using the proposed, ADRC-ADRC structure in the cascade loop. The stability of the proposed controller is presented with Hurwitz’s stability criteria for selecting gains of observers. The results of the proposed controller are compared with the existing active disturbance rejection control-proportional (ADRC-P) and proportional-integral derivative-proportional (PID-P)-based controller by experimental validation.

It is observed that the settling time (ts) in the case of the proposed controller is improved by 60% and 55% in comparison to PID-P and ADRC-P, respectively. The level process is interfaced with an industrial controller and real-time data acquired in matrix laboratory (MATLAB), which acted as a remote monitoring platform for the cascade process.

The proposed controller is designed to provide robustness against disturbance and parameter uncertainty. This paper provides an alternate way for researchers who are using MATLAB and ThingSpeak cloud server as a tool for the implementation.

Although many countries are focusing on the management of construction and demolition waste (CDW) resource utilization, the effect of risk aversion of the green innovation-led enterprise on the performance of the CDW resource utilization supply chain is unclear when considering different green innovation contexts (green innovation led by the building materials remanufacturer or by the construction waste recycler). This study aims to investigate how the level of risk aversion of the green innovation-led enterprise affects CDW resource utilization under different green innovation contexts based on contingency theory.

Using Stackelberg game theory, this study establishes a decision model consisting of a building materials remanufacturer, construction waste recycler and CDW production unit and investigates how the level of risk aversion of the green innovation-led enterprise under different green innovation contexts influences the performance level of the supply chain.

The conclusions are as follows. (1) For the green innovation-led enterprise, the risk-averse behaviour is always detrimental to his own profits. (2) For the follower, the profits of the construction waste recycler are negatively correlated with the level of risk aversion of the green innovation-led enterprise in the case of a small green innovation investment coefficient. If the green innovation investment coefficient is high, the opposite result is obtained. (3) When the green innovation investment coefficient is low, the total supply chain profits decrease as the level of risk aversion of the green innovation-led enterprise increases. When the green innovation investment coefficient is high, total supply chain profit shows an inverted U-shaped trend with respect to the degree of risk aversion of the green innovation-led enterprise.

(1) This study is the first to construct a green innovation context led by different enterprises in the CDW resource utilization supply chain, which provides a new perspective on green management and operation. (2) This study is the first to explore the operation mechanism of the CDW resource utilization supply chain based on contingency theory, which provides new evidence from the CDW resource utilization supply chain to prove contingency theory. At the same time, this study examines the interactive effects of the green innovation cost coefficient and the degree of risk aversion of green innovation-led enterprises on the performance of supply chain members, expanding the contingency theory research on contingencies affecting enterprise performance. (3) This study will guide members of the CDW resource utilization supply chain to rationally face risks and achieve optimal supply chain performance.

Literature reviews in the field of Lean Six Sigma (LSS) are often substantially less stringently portrayed than other empirical research. The purpose of this paper is to lucubrate on clarifying emerging aspects, trends and importance of LSS through reviewing the published literature over multiple parameters for a ameliorating and trenchant view.

In the present study, a literature review of LSS articles is carried out over the time horizon of 14 years from referred peer-reviewed journals in business and management disciplines, information systems and computer science, engineering, healthcare, etc. While carrying out the literature review, various distinct dimensions are considered, such as publication years and journals, countries, research design, research type and application sector within industries. A descriptive evaluation of the literature body is followed by gap identification and future research opportunities.

LSS research is growing rapidly, covering various disciplines and domains with a great focus on LSS tools and techniques; empirical research is dominant with more emphasis on case study approach; and growing gap between manufacturing- and service-focused articles implies return of LSS to manufacturing as its initial base.

The review analysis entirely focuses on descriptive statistics of empirical research in LSS. The sample size includes 189 shortlisted articles in 58 journals published over a time span of 14 years (2001-2014). The paper provides both academicians and practitioners a better panorama to understand the present status of LSS for pursuing rigorous LSS research through explicating chronological emergence, challenging themes, dominating research types and application areas in LSS.

Tech start-ups (TSs) functioning in different domains have a responsibility of ensuring that domestic knowledge and capabilities are leveraged to minimize dependence on foreign organizations. Despite the growth of the ecosystem, while numerous TSs emerge, very few of them are able to survive, and of those that survive, very few scale up. The aim of this study is to identify the factors influencing the competitiveness of technological start-ups and to study the interrelationship and interdependence of these factors.

Modified total interpretative structural modeling (m-TISM) was employed for the current research. The analysis of what factors have an effect on competitiveness, how they affect it and why they affect it should be explored. The study begins by developing the list of factors through literature search, and further it is validated by expert opinion. A hierarchical model has been developed using m-TISM and MICMAC analysis to analyze the driving and dependency power of factors at each level.

Results show that the competitiveness of TSs is affected by organizational agility and internationalization. Factors present at the bottom level, namely entrepreneurial intensity, act as a strong driver for TSs. Team member commitment, transformational leadership, strategic alliances, knowledge sharing and organizational ambidexterity are middle-level factors.

This study is among the few articles that have explored competitiveness of TSs in the Indian context.

Over the last 2 decades, supply chain sustainability research has become a highly dynamic and fruitful study area. This field has garnered significant attention due to its potential to reshape decision-making processes within supply chains. At the same time, the practical side of supply chain operations remains intensely competitive in today’s business landscape. Furthermore, the current academic research aims to outline effective strategies for achieving sustainability across supply chains, particularly in the manufacturing sector. In response to these challenges, this research has conducted an integrated multi-criteria decision-making approach to evaluate sustainable supply chain performance from the triple bottom line perspective, including financial, environmental, and social performance.

The initial stage involves selecting the crucial criteria (short-term and long-term) and alternatives for sustainable supply chain performance (SSCP) from experts and conducting an in-depth literature review. Initially, there were 17 criteria, but after a pilot test with co-authors and online discussions with experts, the number of criteria was subsequently reduced to 9. In the second phase, the Best-Worst Method (BWM) was applied to rank and prioritize the criteria. The third and final stage examined the causal relationship between the identified criteria, utilizing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique.

Based on BWM analysis results, the top three criteria in terms of prominence are: (1) return on investment (ROI), (2) product quality, and (3) manufacturing lead time. Out of the three alternatives, financial performance (FP) is the most crucial dimension for SSCP, followed by environmental performance (ENP) and social performance (SP). On the other hand, the DEMATEL approach showed that work health and safety (short-term criterion), asset utilization (long-term criterion), energy consumption (long-term criterion), waste disposal (long-term criterion), manufacturing lead time (short-term criterion), and on-time delivery (short-term criterion) are categorized within the cause group, while criteria such as return on investment (ROI) (long-term criterion), customer-service level (short-term criterion), and product quality (long-term criterion) fall into the effect group.

The proposed study has certain drawbacks that pave the way for future research directions. First, it is worth noting the need for a larger sample size to ensure the reliability of results, the potential inclusion of additional criteria to enhance the assessment of sustainability performance, and the consideration of a qualitative approach to gain deeper insights into the outcomes. In addition, fuzziness in qualitative subjective perception could be imperative when collecting data to ensure its reliability, as translating experts’ perceptions into exact numerical values can be challenging because human perceptions often carry elements of uncertainty or vagueness. Therefore, fuzzy integrated MCDM frameworks are better suited for future research to handle the uncertainties involved in human perceptions, making it a more appropriate approach for decision-making in scenarios where traditional MCDM methods may prove insufficient.

The proposed framework will enable decision-makers to gain deeper insights into how various decision criteria impact SSCP, thus providing a comprehensive evaluation of SSCP that considers multiple dimensions, such as financial, environmental, and social performance within the manufacturing sector.

The proposed study is the first empirical study to integrate both BWM and DEMATEL approaches to evaluate sustainable supply chain performance in the manufacturing context.

Little is established about the mechanism through which employee voice is connected to employee mental health. Drawing from social exchange theory, this study examines how employee engagement practices are associated with employee voice, which further influences employee mental health. In addition, the study includes parallel mediation and examines whether perceived interpersonal justice (PIJ) and empathetic leadership (EL) mediate the relationship between employee engagement practices and employee voice.

Three time-lagged surveys of 457 employees in the Indian information technology (IT) sector were accomplished.

As hypothesised, employee engagement practices have a positive influence on employee voice. Secondly, employee voice has a positive influence on the employee’s mental health. PIJ and EL were also found to be significant parallel mediators for the relationship among employee engagement practices and employee voice.

This study displays the positive influence of employee engagement practices on employee voice. Further, the employee’s voice influences the employee’s mental health. Therefore, it suggests means for improving its pervasiveness in an organisation.

This research paper is an important contribution as it is one of the few studies examining the role of PIJ and EL as parallel mediators of employee engagement practices and employee voice. It also answers repeated calls for more research on employee mental health in the IT sector.