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This study aims to discover the key performance indicators (KPIs) of the agricultural cold supply chain (ACSC) and analyze their consequences on the performance of ACSC within the bounds of Indian topography.

The KPIs have been explored based on the literature review both in global and Indian context and domain expert's opinions. The interdependency characteristics and cause–effect relationship among the KPIs have been analyzed using a fuzzy decision-making trial and evaluation laboratory (f-DEMATEL) approach.

The findings extracted from the empirical assessment of the problem find strong compliance with the notions of theoretical model assessment. The results highlight that the cost of product waste and operating and performance costs are the two most important performance indicators of an Indian ACSC. Furthermore, governmental policies and regulations and the effectiveness of cold chain (CC) equipment also have a high degree of influencing characteristics on ACSC performance.

To connect the study with practicalities, the assessment of the KPIs is allied with real-time practices by clustering the beliefs of Indian professionals. Therefore, the decision-making behavior of the experts might be influenced by geographical constraints. However, the key findings provide advantages to the ACSC players, a bright hope for future food security and a significant profit for farmers.

The presented paper encompasses various aspects of the ACSC, including theoretical and empirical perspectives exercised to contemplate the system dynamics, which inculcates the essence of the associated practicalities. Thus, this study has various practical contributions relevant to managerial and societal perspectives.

A poor performance of the cold supply chain (CSC) may increase the loss of quality and potency of perishables and temperature-sensitive products that deteriorate the financial and environmental aspects of the same. The purpose of the current research work is to identify the critical performance factors (criteria) and their co-factors (sub-criteria) that are responsible for the performance measurement of CSC and suggest the best possible solutions (alternatives) to improve the same.

To achieve the objective of the research, a hierarchical model has been developed and analyzed using Analytic Hierarchy Process (AHP)-Fuzzy TOPSIS as a hybrid approach to obtain the severity weights of the identified criteria and prioritization toward their relative importance for the best possible alternatives.

Analysis reveals that the criteria “energy consumption” comes out to be the most critical criteria, and alternative “application of passive cold devices” is the most effective solution for improving the performance of CSC. Higher energy consumption leads to a higher rate of greenhouse gas (GHG) emissions increasing the global warming phenomenon, high operational cost and degradation of natural energy resources. The Application of Passive Cold Devices (PCDs) utilizes solar energy to operate the refrigeration units reducing the energy consumption, environmental and operating cost of CSC.

The research work provides several insights into the critical issues related to the CSC and suggests significant findings that enable the management and decision-makers to adopt these practices for performance evaluation and improvement of the same. The key findings of the work, such as “application of passive cold devices” and “application of IoT in cold chain logistics”, facilitate an improved platform to improve the CSC performance and proposed several directions that will enhance the merit of future research.

The presented study consolidates the various perspectives associated with CSC performance, explores the most critical criteria and proposes the best suitable cold chain practices for organizational growth. The work also provides an analytical analysis with the essence of practicalities and sensitivity analysis to support the robustness of the results. By enriching the literature and quantitative analysis of the new proposed model, this paper forms vast managerial and research implications in the field of CSC.

The current study aims to deliver a consolidated view of environmental sustainability in cold supply chain performance systems (CSCPS), incorporating theoretical and empirical analysis for improving environmental standards. For this purpose, this study firstly aims to explore and analyze the various crucial challenging factors for environmental sustainability in the cold supply chain (CSC). Secondly, it discovers the most effective sustainable strategies for improving the environmental sustainability of CSCPS.

The exploration of the crucial challenging factors and the proposed sustainable strategies have been done using a systematic literature review relevant to the sustainable performance of CSC. At the same time, semi-structured brainstorming sessions were conducted with the domain professionals having an industrial and academic background to finalize the strategies. Empirical analysis has been performed using an intuitionistic fuzzy (IF) based hybrid approach of SWARA and COPRAS methods.

The key findings of the study address that “higher energy consumption during refrigerated transportation and storage” is the most crucial challenge for environmental sustainability in CSC. In addition, “managerial refrain to profit decline due to sustainability implementation” is the second most crucial challenge that hinders the adoption of sustainable practices in CSCs. Meanwhile, the governmental attention to motivating organizations for green adoption and implementation of solar energy-driven refrigeration technologies are the two most important discoveries of the study that might help in improving CSC's environmental performance.

From the implications side, the study enriches and extends the current literature content on CSC sustainability. In addition, it offers sound managerial implications by identifying the challenges that create threats among the management for sustainability adoption and suggesting the most suitable sustainable strategies, which may help the management to raise the environmental performance of their CSC. Besides having various important theoretical and managerial implications for the study, contemplation of only environmental sustainability traits as a broader perspective limits the scope of the study.

The study's main contribution is the exploration of the most crucial challenges imparting obstructions in sustainable development and sustainable strategies, which may get the interest of the CSC players, market leaders, and industrial and academic practitioners working in the domain of CSC sustainability. In addition, this study offers structured theoretical and empirical evidence for CSC's environmental sustainability, thus playing a bridging role between theoretical sustainability concepts and its practical implications in CSC industries.

The purpose of this paper is to present a sensitivity analysis of fault-tolerant redundant repairable computing systems with imperfect coverage, reboot and recovery process.

In this investigation, the authors consider the computing system having a finite number of identical working units functioning simultaneously with the provision of standby units. Working and standby units are prone to random failure in nature and are administered by unreliable software, which is also likely to unpredictable failure. The redundant repairable computing system is modeled as a Markovian machine interference problem with exponentially distributed failure rates and service rates. To excerpt the failed unit from the computing system, the system either opts randomized reboot process or leads to recovery delay.

Transient-state probabilities have been determined with which the authors develop various reliability measures, namely reliability/availability, mean time to failure, failure frequency, and so on, and queueing characteristics, namely expected number of failed units, the throughput of the system and so on, for the predictive purpose. To spectacle the practicability of the developed model, a numerical simulation, sensitivity analysis and so on for different parameters have also been done, and the results are summarized in the tables and graphs. The transient results are helpful to analyze the developing model of the system before having the stability of the system. The derived measures give direct insights into parametric decision-making.

The conclusion has been drawn, and future scope is remarked. The present research study would help system analyst and system designer to make a better choice/decision in order to have the economical design and strategy based on the desired mean time to failure, reliability/availability of the systems and other queueing characteristics.

Different from previous investigations, this studied model provides a more accurate assessment of the computing system compared to uncertain environments based on sensitivity analysis.

High throughput and power efficient computing devices are highly essential in many autonomous system-based applications. Since the computational power keeps on increasing in recent years, it is necessary to develop energy efficient static RAM (SRAM) memories with high speed. Nowadays, Static Random-Access Memory cells are predominantly liable to soft errors due to the serious charge which is crucial to trouble a cell because of fewer noise margins, short supply voltages and lesser node capacitances.

Power efficient SRAM design is a major task for improving computing abilities of autonomous systems. In this research, instability is considered as a major issue present in the design of SRAM. Therefore, to eliminate soft errors and balance leakage instability problems, a signal noise margin (SNM) through the level shifter circuit is proposed.

Bias Temperature Instabilities (BTI) are considered as the primary technology for recently combined devices to reduce degradation. The proposed level shifter-based 6T SRAM achieves better results in terms of delay, power and SNM when compared with existing 6T devices and this 6T SRAM-BTI with 7 nm technology is also applicable for low power portable healthcare applications. In biomedical applications, Body Area Networks (BANs) require the power-efficient SRAM design to extend the battery life of BAN sensor nodes.

The proposed method focuses on high speed and power efficient SRAM design for smart ubiquitous sensors. The effect of BTI is almost eliminated in the proposed design.

The study of the success factors of a project is a means of improving the effectiveness of the project. Hence, the purpose of this paper is to identify various determinants and validate their effects on the success of public construction projects in Ethiopia.

The study uses a questionnaire survey to collect data and structural equation modeling (SEM) to empirically examine the effect of determinants, namely, project manager’s competence, owner’s competence, management support and updates, scope clarity (SC), effective partnering, and monitoring and feedback on success of public construction projects which has been measured by performance on cost, schedule, quality and no-dispute parameters. Out of 407 questionnaires distributed among the selected respondents, a total of 200 completed questionnaires were received. The response rate was 49.1 percent.

The results depict that the investigated factors have a significant positive influence on the success of public construction projects with path coefficient of 0.82, the model is substantial in representing the relationship of the factors on the success of public construction projects and the factor “SC” plays a decisive role in the success of a project as it has a path coefficient of 0.98, and it is followed by “effective partnership, and owner’s competency” having equal path coefficients of 0.96.

The proposed model was validated by collecting data from many senior construction executives in Ethiopia only, hence may induce certain bias in the outcome of the study.

The significance of six constructs is highlighted to help the project manager in understanding the role of various constructs in public construction projects. The results would enable researchers and industry practitioners to focus on a few factors to take proactive measures and get the optimum result in the successful delivery of public construction projects. Utilization of SEM in the understanding of the significance of various success determinants is an important contribution to the body of theoretical literature in construction management. Since the model includes constructs, SEM has been used for construct validation.

The implications of this study are not limited to researchers and construction industry practitioners alone. The Ethiopian Government could adopt the results of this study to reduce/avoid additional cost incurred due to the poor performance of public construction projects which results in poor utilization and increased social and economic costs. Furthermore, the study may also help the government efforts to enhance efficiency and effectiveness in the use of public funds for construction projects which are an ongoing concern of government and of the international development community.

This work is original and has neither been published nor under consideration for publication elsewhere. This study can add value to the construction professional in public construction project management as well as the Government of Ethiopia.

The purpose of this paper is to evaluate and rank the success attributes and success factors of the construction organisations.

The viewpoints of the experts engaged in Indian construction industry were used to apply factor analysis and fuzzy preference relation with the help of a questionnaire survey.

The findings indicate that project factor is the most important factor, whereas favourable market and marketing team is the least important factor. Among the success attributes, the availability of qualified staff is the most important attribute, and health and safety management plan is the least important attribute.

Findings of this study are based on the viewpoint of the experts of construction organisations engaged in building projects in India.

The study can be used as a yardstick for the top management of construction organisations to manage their resources efficiently and to develop a strategy to be successful in this business.

Indian construction industry provides direct and indirect employment to the people of India. Hence, the success of construction organisation will contribute to the development of the society and ultimately the nation.

In the earlier studies, researchers have used various statistical tools to identify and evaluate the alternatives for the success factors of construction organisations, but very few of them have tried to assign weights to those alternatives. The simple ranking of alternatives using various statistical analyses, such as mean and standard deviation, relative importance index, etc., is not much useful unless their relative weights are known. With the help of the present study, the authors have tried to overcome the shortcomings of the previous research works.

The purpose of this study is to identify the factors affecting the quality of technical education in a developing nation, India.

Participants were 465 students and 310 faculty members who were randomly chosen from a total of 31 institutions/colleges/universities providing engineering education in Punjab state of India. The factor structures were obtained by applying factor analysis.

The result of this research reveals ten factors determining the quality of technical education, such as teaching practices, infrastructural facilities, industry–institute linkage, faculty's qualification, reputation of the institute, procedural simplification, administrative staff services, access and equity, financial burden of the course and work culture. Moreover, the research results also reveal eight factors affecting the quality of technical education, namely, institutional standards, institutional support, teaching environment, teaching practices, performance-linked promotion, work culture, academic freedom and administrative services in this order of preference are essential for the delivery of quality in technical education.

This study is the first attempt to examine the factor structure of technical education quality from both the perspectives of students and faculty. The implications of this study are expected to help the management of technical education institutes, regulatory agencies and the government in devising strategies to enhance the quality of technical education in India.

The purpose of this paper is to investigate how servant leadership, trust in leader and thriving drive employee creativity.

Using a dyadic sample of 48 teams (each team comprising a supervisor and the subordinates under him), the authors investigated the role of servant leadership in predicting employee creativity, the mediating role of trust in leader and interactive role of thriving therein.

Findings of the study revealed that servant leaders instilled trust within followers, which acted as a mediator in predicting creativity. Further, thriving was found to act as a moderator that influenced the relationship between trust in leader and employee creativity. Findings also indicated that thriving employees exhibited a greater degree of creative behavior when they trusted their leader.

Based on these findings, the study draws the attention of managers toward the role of servant leadership, trust in leaders and thriving in promoting employee creativity.

This is one of the first studies to integrate servant leadership, trust in leader, thriving and creative behavior into a single theoretical model. The study further provides evidence to validate the proposed model in context of predicting employee creativity.

The main aim of the study is to develop a structural framework that includes e-business processes and sustainability-oriented enablers to improve supply chain performance.

To improve supply chain performance, the present study conducts a detailed literature review to explore the key enablers based on e-business processes and sustainability aspects of various recognized databases. An automotive case organization is chosen to conduct a case study for developing the structural framework. The structural framework is developed by adopting an interpretive structural modeling approach. Furthermore, the fuzzy-MICMAC approach is applied to compute the driving and the dependence power of each selected enabler.

This study develops a structural framework that indicates the improved supply chain performance is achieved by “development of supply chain web system,” “strong customer relationship management,” and “enhancement in control over cost quality and sustainability” as the most critical enablers.

The enablers for the development of framework are obtained through the inputs of an expert panel. However, the researchers may conduct large scale surveys to strengthen the input components of the framework.

This is one of the unique studies that list down a set of 27 most critical e-business processes and sustainability based enablers to improve supply chain performance.