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The study aims to add to the body of knowledge of open source tangible product management (also called open design). The objective is also to develop a guideline for efficient open source tangible product development and adoption.

The exploratory research design using secondary data (like newspapers, magazines, research articles, bogs, papers, etc.) is used to analyze open source tangible product design challenges and enablers. The success stories of Open Source Software projects (OSS) were studied for identification of critical success factors and further their relevancy was tested in the two popular cases of open source drug discovery (malaria and tuberculosis)

Open innovation has become a part of competitive strategy of current businesses. It requires an efficient intellectual property protection regime for its implementation. However, in a market dominated by proprietary benefits, the open source technology development can serve as remedy for innovation needs of neglected sectors. The OSS literature revealed managing two classes of factors, namely technology sponsor level factors and environmental factors for efficiency and effectiveness. The case study analysis in the context of applicability of these OSS critical factors showed their limitations in open source tangible products, and highlighted understanding additional challenges and remedies.

Open source innovation is a collaborative effort involving inputs from various/diverse players, hence monitoring the effort and motivation level of the contributors is a cumbersome task. Only the information that is available online and in print media is taken as research inputs in this work. Also the data taken were from two case studies; a lot more case studies in the open design domain can progress the theory. The implications of this study are far-reaching in the areas where profit motivated proprietary efforts lack in addressing societal need. It provides guidelines for addressing those unmet needs by developing products in a collaborative way without intellectual property hurdles.

The essence of open design is becoming more vital, and there is a pressing need to build theory to support it, which still is elusive and dispersed. The study fills the gap using secondary data and case study approach.

This paper develops a decision-analysis model to prioritize and select the site to establish a new hospital over different indicators such as cost, market conditions, environmental factors, government factors, locations and demographics. In this way, an integrated model is proposed under the intuitionistic fuzzy information (IFI), the standard deviation (SD), the rank-sum (RS) and the measurement of alternatives and ranking using the compromise solution (MARCOS) approach for ranking hospital sites (HSs).

The IF-SD-RS model is presented to obtain the combined weight with the objective and subjective weights of diverse sub-criteria and indicators for ranking sites to establish the hospital. The IF-MARCOS model is discussed to prioritize the various sites to establish the hospital over several crucial indicators and sub-criteria.

The authors implement the developed model on a case study of HSs assessment for the construction of new hospital. In this regard, inclusive set of 6 key indicators and 18 sub-criteria are considered for the evaluation of HSs. This study distinguished that HS (h₂) with combined utility function 0.737 achieves highest rank compared to the other three sites for the given information. Sensitivity analysis is discussed with different parameter values of sub-criteria to examine how changes in weight parameter ratings of the sub-criteria affect the prioritization of the options. Finally, comparative discussion is made with the diverse extant models to show the reasonability of the developed method.

This study aims to develop an original hybrid weighting tool called the IF-SD-RS model with the integration of IF-SD and IF-RS approaches to find the indicators' weights for prioritizing HSs. The developed integrated weighting model provides objective weight by IF-SD and subjective weight with the IF-RS model. The model presented in the paper deals with a consistent multi-attribute decision analysis (MADA) concerning the relations between indicators and sub-criteria for choosing the appropriate options using the developed IF-SD-RS-MARCOS model.

The purpose of this study is to examine how Industry 4.0 (I4.0) implementation might improve marketing performance (MP). Early adopters now have the chance to capitalize on the advantages of this successful implementation owing to the transition to I4.0. To improve MP, businesses must be able to identify and manage their effective implementation of I4.0 technologies, which are essential to improve industrial performance.

A survey was created and sent to 311 samples of manufacturing companies. To investigate the hypothesis created in this context, the study includes a survey-based analysis. To present the study’s findings, partial least squares-structural equation modeling has been used.

According to the findings, it can be concluded that an efficient implementation of Industry 4.0 (EII) can improve MP by positively impacting consumer loyalty and increasing customer loyalty (CL) positively enhancing by product customization (PC). The study’s key results, however, are how both PC and CL affect MP.

The intensive production technologies that are at the center of I4.0 will be better understood by professionals thanks to this study. The Internet of Things, artificial intelligence, additive manufacturing, sophisticated robots and many more are examples of these technologies. I4.0’s application strengthens efficiency and high-quality production. The I4.0 concept is gaining popularity in both developed and emerging countries due to its higher performance. Additionally, business people are actively working to implement I4.0 and make it a big success.

The study identifies the successful adoption of I4.0 that has a substantial impact on businesses’ MP. However, there is a lack of noteworthy studies that can concentrate on the marketing reach with I4.0 deployment. As a result, the goal of the current research is to comprehend how I4.0 will affect MP.

Small and medium-sized enterprises (SMEs) are a major source of employment and revenue growth in developing nations like India, but they also face challenges from resource shortages, shifting consumer demand and heightened competition. This research aims to discover the aspects that enhance SMEs' competitiveness and performance.

By analyzing literature and consulting experts, 10 factors that boost a firm's competitiveness were identified. The total interpretive structural modeling (TISM) method was then used to determine their interaction and structural hierarchy. Neutrosophic-MICMAC analysis was employed to assess the driving-dependence power of each factor.

The study discovered that the factor, namely “entrepreneurial orientation,” was found to be a significant one. “Manufacturing strategy” was found to be extremely dependent on the remaining competitive advantage factors.

This SME-focused framework can be adopted by large businesses to enhance organizational performance by focusing on critical factors. The study depends on experts' judgment, which might be biased. Findings will assist SMEs in identifying significant factors influencing competitive advantage and relationships, increasing awareness of factors contributing to competitive edge.

The results of the research may encourage SME sector managers and practitioners to prioritize the factors that contribute to a firm's competitive advantage.

The majority of research on SME competitive advantage focuses on individual aspects. To add to the body of knowledge on the subject, this study applies the TISM technique to Indian SMEs to identify the contextual interactions among factors that increase long-term competitiveness.

This study aims to examine the implementation of agile practices in Industry 4.0 to assess the financial performance measurements of manufacturing firms. It also investigates the relationship between supply chain performance and financial performance.

The study is based on an experimental research design by collecting data from 329 responses from key officials of manufacturing firms. The analyses are carried out to explore this modern concept with the help of the SPSS program, which is used to conduct a confirmatory factor and reliability analysis and Smart-partial least square (PLS) version 4.0 with structural equation modeling.

This research demonstrates the positive effect agile supply chain strategies in Industry 4.0 may have on manufacturing companies' financial performance as a whole. Everything throughout the supply chain in Industry 4.0, from the manufacturers to the end users, is taken into account as a potential performance booster. The values obtained from the model's study show that it is both dependable and effective, surpassing the threshold for such claims. The research is supported by factors like customer involvement (CUS), continuous improvement (CI), integration (INT), modularity (MOD), management style (MS) and supplier involvement (SI) but is undermined by factors including postponement (PPT).

According to the findings of the study, Industry 4.0 firms' financial performance and overall competitiveness are significantly improved when their supply chains are more agile. A more agile supply chain helps businesses to more rapidly adapt to shifts in consumer demand, shorten the amount of time it takes to produce a product, enhance product quality and boost customer happiness. As a consequence of this, there will be an increase in revenue, an improvement in profitability and continued sustainable growth.

There are literary works available on agile practices in various fields, but the current study outlines the need to understand how supply chains perform financially under the mediating effect of agile supply chains in Industry 4.0 which contribute most to the organization's success. The study will aid companies in understanding how agile practices will further the overall performance of the organization financially.

This study aims to explore customers’ second-hand clothing purchases and their engagement on the Facebook marketplace.

A conceptual model is developed, building upon the online second-hand shopping motivation (OSSM) scale. Data gathered from 409 respondents was analysed using covariance-based structural equation modelling.

The results highlight that economic, convenience, ideological motivations and environmental concerns impact customers’ purchase intention. Conversely, status consumption was found to impede customers’ purchase intentions. Notably, the elements of social media engagement, including consumption, contribution and creation, demonstrated significance as a consequence of customers’ second-hand clothing purchase intention.

This study’s findings contribute to the knowledge encompassing sustainable fashion consumption, information systems and second-hand social media shopping. It uniquely explores customer behaviours related to second-hand clothes shopping on the Facebook marketplace by building upon the OSSM scale. These findings offer valuable insights, showcasing the determinants that can increase customer-centric social media engagement. These results inform online retailers on Facebook marketplace about sustainable practices, aligning with UN Sustainable Development Goals 12, 13 and 8, to promote a green global economy.

This study investigates the supply chain efficiency of selected companies in the Indian food processing sector. Additionally, it explores the relationship between supply chain efficiency and firm performance.

To determine the supply chain efficiency, the study uses supply chain efficiency measures, such as supply chain length, inefficiency ratio and working capital productivity. Secondary data were collected from the Center for Monitoring Indian Economy (CMIE) Prowess database for the years 2011–2017. Various return measures, such as Return on Net Worth (RONW), Return on Total Assets (ROTA) and Return on Capital Employed (ROCE), were used to measure firm performance. Collected data were analyzed to investigate the relationship between supply chain efficiency and firm performance.

Findings of the study reveal the prevalence of inefficient supply chains in the context of the selected companies. There is a significant negative correlation between supply chain efficiency and firm performance. RONW has a significant negative correlation with the length of supply chain as well as supply chain inefficiency.

This study expands the limited existing research perspective; the study helps to understand the supply chain efficiency and firm performance.

This is an original piece of work and provides valuable insight into the relationship between supply chain efficiency and firm performance.

This study aims to explore the global issues of impulse buying, compulsive purchasing and materialism. It examines how materialism relates to self-esteem and the tendencies for impulsive and compulsive buying. In addition, the study delves into the impact of religiosity on self-esteem and materialistic values in an Islamic country.

Enumerators visited universities, distributing 415 questionnaires and receiving 397 in return. Due to the unavailability of a sample frame for the target population, the study used nonprobability sampling for statistical analysis, which included assessments of normality, reliability, validity and bootstrapping for the structural model, the researchers used Smart PLS.

The study confirmed 13 hypotheses while rejecting four. The unsupported hypotheses are: (i) materialism negatively impacts impulsive purchasing behavior, (ii) impulsive purchasing does not mediate the relationship between materialism and compulsive purchasing, (iii) materialism does not mediate the relationship between religiosity and impulsive purchasing and (iv) in an Islamic country, neither materialism nor impulsive purchasing significantly mediates the relationship between religiosity and compulsive purchasing.

This study was conducted in a city within a developing Islamic nation, focusing on college students. It suggests that future research could include more cities, a diverse population segments and multicultural perspectives. The research primarily examined the direct relationships between religiosity and factors such as self-esteem, materialism and impulsive purchasing. Future studies could explore religiosity as a mediating factor. This study highlights that materialism (M), impulsive buying (IB) and compulsive buying (CB) are not only closely interconnected but also adversely affect individual, family and societal well-being, raising global concerns. While occasional impulsive behavior is common among individuals in Islamic nations, repeated indulgences in the same behavior could lead to an obsession with excessive purchasing.

This study holds significant implications for consumers and retailers. Excessive and unnecessary spending can increase financial burden and adversely affect family welfare. Often, families and acquaintances inadvertently teach children to engage in extreme purchasing behaviors. To combat this, families and religious leaders should educate individuals about the detrimental effects of impulsive and compulsive purchasing. In addition, colleges and other institutions should organize seminars and workshops to address these issues. Retailers, whose sales largely depend on impulsive and compulsive consumers, should employ interpersonal influencers and brand advocates to connect with this customer segment effectively.

This study examined the relationship between religiosity, materialism, self-esteem and impulsive and compulsive purchasing behaviors. This study thoroughly tested 17 hypotheses, encompassing direct, mediating and multimediating relationships. The findings reveal that materialism’s impact on impulsive behavior is negligible compared to previous research, corroborating the findings presented in the cited literature.

A learning-focused culture promotes creativity, innovativeness and the acquisition of novel insights and competencies. The study aims to explore the relationship between human resource development (HRD) practice and employee competencies using organizational learning culture as a mediating variable.

Data were collected from 828 employees of 37 health care institutions comprising 24 (internationally-owned) and 13 (indigenously-owned). Construct reliability and validity was established through a confirmatory factor analysis. The proposed model and hypotheses were evaluated using structural equation modeling.

Data supported the hypothesized relationships. The results show that training and development and employee competencies were significantly related. Career development and employee competencies were significantly related. Organizational learning culture mediates the relationship between training and development and employee competencies. However, organizational learning culture did not mediate the relationship between career development and employee competencies.

The generalizability of the findings will be constrained due to the research’s health care focus and cross-sectional data.

The study’s findings will serve as valuable pointers to policy makers and stakeholders of health care institutions in developing system-level capacities that promote continuous learning and adaptive learning cultures to ensure sustainability and competitive advantage.

By evidencing empirically that organizational learning culture mediates the relationship between HRD practices and employee competencies the study extends the literature.

Employee engagement (EE) continues to be one of the most difficult challenges for organizations today. Numerous factors have been linked to EE, according to studies. However, the necessary human resource management (HRM) strategies and systems for enhancing EE have not yet been developed. It is questionable if all employees inside the company require the same HRM strategies, to boost engagement as one size does not fit all. Therefore, it is necessary to create employee profiles based on factors associated with EE. This study aims to develop employee profiles based on engagement dimensions and outcomes. It seeks to comprehend the relationship between engagement level and factors such as age, years of service and employment grade.

Using latent profile analysis (LPA), we identified five EE profiles (highly engaged, engaged, moderately engaged, disengaged and highly disengaged). These five profiles were characterized by five EE dimensions (Culture Dimensions, Leadership Dimensions, People Process, Business alignment Dimension and Job Dimension) and EE outcomes (Say, Stay and Strive).

The study revealed that Engaged profiles exhibited low stay outcomes. The highest percentage of disengaged employees fall under 25 years of age with less than 5 years of experience and are at the entry level.

The study highlights the significance of the people processes dimensions in enhancing engagement. Profiles with low people process dimensions showed high disengagement. Person-centered LPA adds and complements variable-centered approach to develop a better understanding of EE and help organizations devise more personalized strategies. The study would be of interest to both academics and practitioners.

The novelty of this study lies in its attempt to model the employee profiles to comprehend the relationship between engagement levels using LPA.