Search results

This study aims to explore supply chain resilience (SCR) and provides a unique resilience index. The work measures the resilience status of 37 organizations across 22 industries and provides insight into accessing the supply chain (SC) vulnerability in an uncertain environment.

This study involves measuring the resilience status of 37 organizations across 22 industries based on a subjective decision-making approach using fuzzy logic. Experts from industries rated the importance and level of implementation of 33 attributes of SCR, which are used to develop a fuzzy index of implementation that explains the resilience status of organizations.

A novel coexistent resilience index is computed based on mutualism to exhibit the proportion of contribution or learning of each attribute of an organization in an industry. The research will enhance the response plans and formation of strategic alliances for mutual coexistence by industry.

Evidence-based interpretations and suggestions are provided for each industry to enhance resilience through coexistence.

The work uniquely contributes to academic literature and SC strategy. The novel coexistent resilience index is computed based on mutualism, facilitating researchers to access SC resiliency.

Over the last two decades, green supply chain management (GSCM) has enabled businesses to operate in an environmentally friendly manner. The present review examines 234 research articles and proposes a methodical literature review on GSCM, focusing on the aspects of sustainable development.

The work examines conceptual, analytical, empirical and non-empirical research articles, analyzing at all levels of the organization, such as firm, dyad, supply chain and network. The objective of the review is to provide insights into the state and scope of existing research in the domain of GSCM, to identify the prevalence of GSCM and to consolidate the trend of future research. The literature review follows a systematic methodology for analyzing the literature.

The findings can support researchers in identifying research areas with significant impact and streamline research on GSCM in the future. Practitioners can utilize this structured classification to strategize their green initiatives in their firms.

The work contributes to providing literature that explores a detailed review in GSCM. The proposed literature review captures critical aspects in the domain of GSCM and offers future research directions.

The textile industry contributes 2 and 3% to the global and Indian Gross Domestic Product (GDP), respectively. India supplies a quarter of global cotton yarn. Yet, most yarn manufacturing companies use outdated methods and lack organisational skills and strategies. Improvement in processes in India could significantly help the industry worldwide.

The variables that influence the performance of the system were identified. Their interrelationships and impact were identified from the employees in the chosen case study, a yarn manufacturing industry. A System Dynamics (SD) approach was employed to study the benefits of implementing 5S lean strategies. The impact of each variable on various performance measures such as throughput, Work In Progress, processing time, waiting time, idle time, over-processing and scraps was analysed.

Improvement in outcomes reflected an enhanced adoption of leanness in the industry. The decision-makers can utilise this study to optimise the necessary parameters in the system and attain the desired productivity levels. Better resource management and reduced processing time helped increase the despatch rate by 9.735% and decrease the WIP by 23.01%. Time management helped to reduce the inventory, idle time and waiting time. Over-processing, defects and scraps were minimised, indicating a shift towards lean.

This study pioneers the use of SD simulation models for optimising yarn manufacturing using lean strategies. Improvement in performance measures by integrating these strategies opens avenues for future research using multiple approaches to address a problem.

Implementing 5S lean principles and simulations enhances productivity, reduces waste and optimises resource management for the yarn manufacturing industry. Decision-makers can employ simulation to witness the outcomes of their changes without investing cost and time and without associated implementation risks.

The use of a simulation model to witness the benefits of incorporating lean strategies in yarn production has not been explored. This approach could help the managers and policymakers understand their existing system's shortcomings and critical areas that require improvement.

The paper aims to analyse the postharvest Supply Chain (SC) of tomatoes to maximise profit by restructuring the modes of operation.

System Dynamics-based simulation of four scenarios depicting different operational modes of postharvest food SC was employed. Real-time of Tamil Nadu state, India was used to enact the scenarios using Vensim.

Results indicated that cold storage improved the profit of wholesalers by prolonging the shelf-life of commodities. Retailers and farmers gained more profit in the absence of wholesalers. Though the absence of middlemen reduces the transit time and prevents deterioration, the role of wholesalers, i.e. transporting the commodities to farther customers’ needs to be shouldered by other agents effectively to minimise losses.

The accuracy of the results depend on the exactness of the data collected. The simulation findings, on the other hand, could be helpful in decision-making as these models portray the actual operational modes of postharvest SC. The suitability of each network structure depends on the capabilities of the agents, market scenario and demography. Implications based on discussions with stakeholders and in terms of establishing dedicated societies (cooperatives) have been provided.

Postharvest losses incurred for horticultural crops like tomatoes are significantly high. It is of much importance to India as agriculture contributes to 17% of the Gross Domestic Product (GDP) and India is the second-largest producer of tomatoes globally. The study would shed light on restructuring the network appropriately.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

Agricultural sector not only meets the nutritional requirements of all living creatures but also generates the primary source of the raw material provided by various branches of industry to fulfill their functions. It is of great importance to increase studies on oilseeds which have an important role in Turkey's agricultural products. They are grown in almost all of the country, which are vital for the nutrition and many sectors. The main purpose of the study is to offer an integrated approach to determine potential warehouse locations for oilseeds.

This is the first study that integrates Delphi, analytical hierarchical process (AHP), technique for order preference by similarity to ideal solution (TOPSIS), P-Median and Panel data analysis in a real case. This integrated approach consists of the following steps, respectively: (1) The criteria were determined by the Delphi method. (2) The weights of the criteria were calculated by AHP and the provinces with the highest oilseed warehouse potential in seven regions of Turkey were specified by TOPSIS. (3) Oilseed warehouse numbers and locations were obtained by P-Median. (4) In order to answer whether the distribution network is profitable in the future with the determined center locations, a forecast model based on panel data analysis was created. (5) Regional representatives were determined for 2030, and the distribution network was analyzed again. (6) The costs that arose in 2018 and 2030 were computed and compared by cost analysis. (7) The effect of the change in criteria weights on the alternative results was tested by scenario analysis.

The findings indicated that oilseed crop production potential and oilseed crop production area turned out to be the most important criteria. Furthermore, the results showed that this model is robust and suitable for warehouse location selection studies.

The study can serve as a guide for local and central policy makers with both the criteria it uses and the model it develops.

The main contribution of this study is that the integrated approach has been used for the first time in location selection in a real case.

This study aims to explore the empirical correlation between patient flow issues, quality of green health services and patient satisfaction in specialist medical department factors from patients’ perspectives as service consumers.

This research is a type of nonintervention empirical research that uses an open survey to explore the views and experiences of users of specialist medical department services. The targeted population is hospital patients included in the top five national PERSI (Indonesian Hospital Association) Award 2022 Green Hospital Category, with a total number of respondents of 572 people. This study uses the partial least square-structural equation modeling analysis method with the SmartPLS application.

Patient flow problems generally affect the quality of eco-friendly health services, except for the waiting time problem, which affects service quality. It should be understood as a top priority for patients to receive services from medical specialists without risking time as a core service aspect from the patient’s perspective. In addition, all variables in eco-friendly hospital services affect patient satisfaction, except in the case of visits to specialist medical departments, which do not affect medical support services and hospital practices that are responsive to the delivery of care services resulting from medical support services that are inseparable in integrated services as well as health care following medical ethics.

This study has a novelty in understanding the implications of green practice in determining patient satisfaction in medical specialist department as the epicenter of hospital services and the main object of assessment for the quality of hospital services.

To coordinate humanitarian organisations with different mandates that flock the scenes of disasters to save lives and respond to varied needs arising from the increased number of victims is not easy. Therefore, the level at which organisations self-organise, network and adapt to the dynamic operational environment may be related to inter-organisational coordination. The authors studied self-organisation, organisational networks and adaptability as important and often overlooked organisational factors hypothesised to be related to inter-organisational coordination in the context of humanitarian organisations.

The study’s sample consisted of 101 humanitarian organisations with 315 respondents. To decrease the problem of common method variance, the authors split the samples within each humanitarian organisation into two subsamples: one subsample was used for the measurement of self-organisation, organisational network and adaptability, while the other was for the measurement of inter-organisational coordination.

The partial least square structural equation modelling (PLS-SEM) analysis using SmartPLS 3.2.8 indicated that self-organisation is related to inter-organisational coordination. Organisational network and adaptability were found to be mediators for the relationship between self-organisation and inter-organisational coordination and all combined accounted for 57.8% variance in inter-organisational coordination.

The study was cross sectional, hence imposing a limitation on changes in perceptions over time. Perhaps, a longitudinal study in future is desirable. Data were collected only from humanitarian organisations that had delivered relief to refugees in the stated camps by 2018. Above all, this study considered self-organisation, adaptability and organisational networks in the explanation of inter-organisational coordination, although there are other factors that could still be explored.

A potential implication is that humanitarian organisations which need to coordinate with others in emergency situations may need to examine their ability to self-organise, network and adapt.

Social transformation is a function of active social entities that cannot work in isolation. Hence, for each to be able to make a contribution to meaningful social change, there is need to develop organisational networks with sister organisations so as to secure rare resources that facilitate change efforts coupled with the ability to reorganise themselves and adapt to changing environmental circumstances.

The paper examines (1) the extent to which self-organisation, adaptability and organisational networks influence inter-organisational coordination; (2) the mediating role of both adaptability and organisational networks between self-organisation and inter-organisational coordination in the context of humanitarian organisations against the backdrop of complex adaptive system (CAS) theory.

Focusing on the Indian context, with the increase in the amount of data and its analysis in health-care knowledge management (KM), the privacy concerns rise which results in loss of trust of an individual in e-health-care systems. Privacy issues in health care, specific to India, are caused by prevalent complacency, culture, politics, budget limitations, large population and infrastructures. Because of these factors, data security requires a backseat that allows easy access to confidential information. Furthermore, the prevalent culture affects health-care disclosure in India. In many cultures, disclosing sensitive personal health-care data is considered ill mannered. This leads to discrepancies in the recorded health-care data and a decrease in the level of treatment meted out. The results and statistics of treatments given do not match the records because of inaccurate data reporting. With the significant rise in the analysis and use of technology in health-care KM systems, it is important to understand the perception of KM in terms of its use and awareness about data sharing in the KM system. The purpose of the paper is to measure the perception of privacy issues in the context of Indian healthcare management systems.

To measure the perception of the use of the KM system, a set of 20 questions was circulated with a sample size of 337 which includes health-care researchers, doctors, practitioners and patients. The questions focused upon the use, share the sensitive health data in the KM platform. All the demographic information such as age, sex, religion, occupation is recorded. The privacy of the individual is maintained while circulating the questionnaire. The usage of health KM system and its privacy is measured through means and t-test.

The results of the t-test were found positive. This research study finds that the privacy factor is important among the Indians to share the information with the KM repository. It is also found that medical practitioners or data custodians are not much serious about sensitive data is being stored for analysis. From the statistical perception of usage of KM and its privacy, new architecture and privacy guidelines were suggested which can be considered in future research.

From the literature review, the questionnaire has developed which can help policymakers and hospital administrators collect information about KM processes in health-care organizations, and this can result in higher performance of health organizations. The privacy factor can also be included in typical health KM architecture ensure that while knowledge acquisition process, privacy of individual or organization can be maintained.

KM enhances the value of corporations and business industries through knowledge production, distribution and provides reliable access to the knowledge resources. KM in health care can comprise a confluence of formal methodologies and techniques to facilitate the creation, identification, acquisition, development, preservation, dissemination and finally the utilization of the various facets of a health-care enterprise’s knowledge assets. According to IBM Global executive report in the year 2012, the entire health-care system has changed from diseases-centric to patient-centric. India is emerging in terms of revenue and employment in the health-care field. The advances of information and communication technology help the health-care sector streamline for data structure and access and health analytics.

In India, the KM is frequently used in health-care industries majorly by health-care practitioners and professionals. As health-care data and knowledge are considered to be sensitive, the privacy of an individual while using the data cannot be compromised. The proposed empirical work will provide a solution in determining the main barriers of implementing privacy policies that need to be solved first and to ensure effective implementation of KM in the health care of India.

Recently, interest in sustainability has grown globally in the heavy vehicle and equipment industry (HVEI). However, this industry's complexity poses a challenge to the implementation of generic sustainable supply chain management (SSCM) practices. This study aims to identify SSCM's barriers, practices and performance (BPP) indicators in the HVEI context.

The results are derived from case studies of four multinational manufacturers. Within-case and cross-case analyses were conducted to categorise the SSCM BPP indicators that are unique to HVEI supply chains.

This study's analysis revealed that supply chain cost implications and a deficient information flow between focal firms and supply chain partners are the key barriers to SSCM in the HVEI. This analysis also revealed a set of policies, programmes and procedures that manufacturers have adopted to address SSCM barriers. The most common SSCM performance indicators included eco-portfolio sales to assess economic performance, health and safety indicators for social sustainability and carbon- and energy-related measures for environmental sustainability.

The insights can help HVEI firms understand and overcome the typical SSCM barriers in their industry and develop, deploy and optimise their SSCM strategies and practices. Managers can use this knowledge to identify appropriate mechanisms with which to accelerate their transition into a sustainable business and effectively measure performance outcomes.

The extant SSCM literature has focused on the light vehicle industry, and it has lacked a concrete examination of HVEI supply chains' sustainability BPP. This study develops a framework that simultaneously analyses SSCM BPP in the HVEI.