Search results

Two key questions in flexible manufacturing systems design are “Why and where is flexibility needed?” and “What type of flexibility is needed?” We present an auditing tool to support managers in their efforts to answer these questions. The objective of this audit is to estimate the needed flexibility by linking it to the uncertainty experienced in the company’s manufacturing operations. The premise of this approach is that the need for flexibility is triggered by some recurring operational change in the company’s environment. Introduces two distinct classes of flexibility‐related changes on the basis of their source: external and internal. The flexibility audit consists of a structured questionnaire that is designed to identify and prioritize the changes being experienced by the facility. Subsequently prioritizes and links the changes to different flexibility types. Reports the results of the audit in three easy to read tables. Expects the audit to be the first step in any flexible manufacturing design (FMD) effort. Presents a case study.

The purpose of this paper is to examine the relationships of service marketing mix (SMM) as service input and service output in terms of students’ performance, satisfaction and referral act in context to higher and technical education (HTE) through the application of structural equation modeling.

A quantitative research, conducted through a self-administered survey composed by a closed-ended structured questionnaire, was incorporated for the students who were enrolled in the technical educational institutions situated in the Khandesh region of India.

The findings of this study revealed that traditional SMM is statistically linked with the performance of students in terms of skill and knowledge enhancement, satisfaction and referral act of students, which are perceptible new emerging SMM; performance, pleasure and pointing out in terms of service output.

Integrating SMM as service input and service output are productive for HTE in enhancing growth (quantitatively) by the inclusivity of diversified students and development (qualitatively) by enhancing their performance for global standing, making them satisfied and motivating them for recommending their institution to others. This integration can be utilized as a yardstick by the institutions for staying ahead in students’ market with a distinctive competitive advantage.

Growth and development of HTE will raise a society’s quality of life and thereby increase a country’s socio-economic status.

The study has exhibited SMM as input and output of a service system that is useful for the growth and development of HTE. The measurement tool presented is effective in (re)framing policies on SMM as service input based on desired service output.

Many engineering applications in this era require new age materials; however, some classic alloys like spring steel are still used in critical applications such as aerospace, defense and automobile. To machine spring steel material, there exist various difficulties such as rapid tool wear rate, the rough surface formation of a workpiece and higher power consumption. The purpose of this paper is to address these issues, various approaches in addition to electrical discharge machines (EDM) are used such as dry EDM (DEDM) and near dry EDM (NDEDM).

This study focuses on these two approaches and their comparative analysis with respect to tool wear during machining of spring steel material. For this study, current, gap voltage, cycle time and dielectric medium pressure are considered input variables. This study shows that the near dry EDM approach yields better results. Hence, the thermo-electrical model for this approach is developed using ANSYS workbench, which is further validated by comparing with experimental results. This thermo-electrical model covers spark radius variation and formation of temperature profile due to electric discharge. Transient thermal analysis is used to simulate the electric discharge machining.

It is observed from this study that discharge environment parameters such as debris concentration and fluid viscosity largely influences the dielectric fluid pressure value. Experimental results revealed that NDEDM yields better results in comparison with DEDM as it shows a 25% lesser tool wear rate in NDEDM.

The range of predicted results and the experimental results are in close agreement, authenticating the model.

Bicycle sharing offers a novel way to create smart and sustainable mobility solutions for the future. The purpose of this study is to draw on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) framework for identifying the factors necessary to predict bike-sharing intention among users in India.

Data were collected through a questionnaire distributed across four major cities in India, and 515 responses were analyzed. A sequential approach was employed to analyze the data using Partial Least Square–Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA).

The findings from PLS analysis revealed that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation and price value are the salient variables that affect users' intentions to participate in bike sharing. In addition, based on fsQCA, six configurations of causal conditions are presented as intermediate solutions that produce the same results. Although antecedent conditions, such as habit and social influence, had an insignificant effect on individuals' BSI, they create conditions sufficient to encourage users' participation in bike sharing in combination with other variables.

A few limitations of this research and the implications of the findings in terms of theory and policy implications are also discussed.

The reported study is one of the earliest to explain bike-sharing adoption in India using the UTAUT 2 model.

The purpose of this paper is to determine the effectiveness of community outreach efforts in promoting public education on the early warning signs of psychosis and in generating referrals for treatment during the prodromal stage of illness.

Five mental health centres across the United States implemented a community outreach model known as the Early Detection and Intervention for the Prevention of Psychosis Program (EDIPPP). A multi‐site evaluation was conducted to assess whether the model's outreach objectives could be achieved among replication sites in geographically and demographically diverse locations. The assessment included the analysis of data from three main sources: administrative data, structured qualitative interviews, and participant self‐report surveys.

Results demonstrated that the outreach activities in all five sites resulted in increased awareness of participants about the early warning signs of psychosis, the availability of local treatment options and increased knowledge of the referral process. There were benefits of outreach participation regardless of whether the participant was a professional or non‐professional in the community. Additionally, outreach participants showed a significant increase in their likelihood to refer a young adult for a mental health evaluation.

Community outreach can be an effective tool for mental health centres in developing a local network that can generate timely referrals for early intervention programmes and clinical research. Results also show that relatively brief community engagement efforts can significantly increase the knowledge and awareness of the public on complex mental health conditions where early detection may be integral to effective treatment.

This study aims to examine the effects of three green information quality dimensions – persuasiveness, completeness and credibility – on green brand evaluation and whether this is mediated by green brand credibility. It also examines the moderating effects of eco-label credibility and consumer knowledge on green information quality dimensions and green brand credibility relationships.

Using a structured questionnaire on environmentally-friendly electrical goods/electronics, cosmetic and apparel product advertisements, involving an elaboration task, this study collected usable data from 1,282 Indian consumers across 50 cities. It also undertook an assessment for three different product groups using structural equation modelling to examine proposed hypotheses and assessed moderated mediation using the Hays process model.

The study indicates that: green brand credibility mediates the effects of green information quality dimensions on green brand evaluation; consumer knowledge moderates the effects of persuasiveness and completeness on green brand credibility and eco-label credibility moderates the effects of persuasiveness and credibility on green brand credibility.

In green information processing, this study supports the relevance of the elaboration likelihood model and the mediation effect of green brand credibility. It also presents evidence that credible eco-labels enhance green information processing. While the results are broadly consistent across the three product categories, the results may only generalizable to the environmentally-aware urban populations.

Help brand managers to design advertisements that add brand credibility in environmentally-aware urban markets.

It helps to define green information quality and the interacting effects of eco-label credibility and consumer knowledge in green information processing.

It is well-known that women scientists are few in numbers in prestigious research organizations and still fewer in leadership positions. The purpose of this article is to analyze how organizational gender inequality is rationalized by scientists so as to highlight how discourse on equality reproduces gender at the workplace.

Data was collected through semi-structured face-to-face interviews with the scientists in four research laboratories dealing with medicinal drugs and chemical substances. It uses discourse analysis by Foucault as a theoretical lens to examine how gender inequality is rationalized and the power relations behind it. It adopts the perspective that socio-cultural beliefs form the basis of gendered practices in organizations.

It finds that the scientists refuse to blame the organization for inequalities by delinking gender issues from the organizational domain. This delinking occurs through rationalizing gender inequality as “social”, through separating informal behavior from the “system” and perceiving women as “privileged”. Such discourses while keeping intact the rationality and meritocracy of the organizations/institutions, reproduce the ideological “public-private dichotomy” and the male dominance at the workplace.

The findings indicate the need for extensive studies in India highlighting how gender is done in organizations, exploring men's role in undoing gender and government initiatives to create a climate of gender equality.

It highlights how discourse on gender equality/inequality at the workplace manifests dominance of men and represents an intersection of Indian social, organizational and institutional contexts at workplace. It also calls into question the applicability of the western concepts of “individualization” and “gender fatigue” to the Indian context.

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

The advancements in internet technologies and the use of sophisticated digital devices in supply chain operations incessantly generate enormous amounts of data, which is termed as big data (BD). The BD technologies have brought about a paradigm shift in the supply chain decision-making towards profitability and sustainability. The aim of this work is to address the issue of implementation of the big data analytics (BDA) in sustainable supply chain management (SSCM) by identifying the relevant factors and developing a structural model for this purpose.

Through a comprehensive literature review and experts’ opinion, the crucial factors are found using the PESTEL framework, which covers political, economic, social, technological, environmental and legal factors. The structural model is developed based on the results of the total interpretive structural modelling (TISM) procedure and MICMAC analysis.

The policy support regarding IT, culture of data-based decision-making, inappropriate selection of BDA technologies and the laws related to data security and privacy are found to affect most of the other factors. Also, the company’s vision towards environmental performance and willingness for material and energy optimization are found to be crucial for the environmental and social sustainability of the supply chain.

The study is focused on the manufacturing supply chain in emerging economies. It may be extended to other industry sectors and geographical areas. Also, additional factors may be included to make the model more robust.

The proposed model imparts an understanding of the relative importance and interrelationship of factors. This may be useful to managers to assess their strengths and weaknesses and ascertain their priorities in the context of their organization for developing a suitable investment plan.

The study establishes the importance of BDA for conservation and management of energy and material. This is crucial to develop strategies for enhancing eco-efficiency of the supply chain, which in turn enhances the economic returns for the society.

This study addresses the implementation of BDA in SSCM in the context of emerging economies. It uses the PESTEL framework for identifying the factors, which is a comprehensive framework for strategic planning and decision-making. This study makes use of the TISM methodology for model development and deliberates on the social and environmental implications too, apart from theoretical and managerial implications.

The purpose of this paper is to capture the status of implementation of Six Sigma in various manufacturing industries and also examine the success of the Six Sigma by using different performance indicators.

The methodology of critical review involves the selection and classification of 112 research articles on the implementation of Six Sigma in different manufacturing industries. The selected articles are categorized by the following: articles distribution based on the year of publication, publication database, various journals, contribution of authors, continent, scale of industry, implemented approaches, focused industry, tools and techniques used in phases of Six Sigma methodology, and performance indicators used in Six Sigma implementation. Then after, future scopes of research opportunities are derived based on significant findings.

The literature revealed that: Very few work was undertaken on the implementation of Six Sigma in various manufacturing industries like ceramic, paper, gems and jewelry, cement, furniture, stone, fertilizer, forging, paper and surface treatment industries. Most of the researchers have considered very few performance indicators to identify the improvement after Six Sigma implementation. But, there is no clue regarding overall improvement in different perspectives after the implementation of Six Sigma. The financial indicators, personnel indicators, process indicators and customer indicators are useful to measure the overall improvement after the implementation of Six Sigma in the manufacturing sector.

The study was carried out on the implementation of Six Sigma methodology in various manufacturing industries, and various performance indicators were identified while implementing the Six Sigma methodology. Case studies pertaining to service industries were not covered here.

Very little research has been carried out to measure the overall success of implementing Six Sigma methodology in manufacturing industries. This paper will provide value to students, researchers and practitioners of Six Sigma by providing insight into the implementation of Six Sigma in manufacturing industries.