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The purpose of the present work is identification and prioritization of barriers to Lean Six Sigma (LSS) implementation in Indian manufacturing industries in the context of Industry 4.0 (I4.0) to surmount the impediments in the path of successful implementation.

In total, 27 barriers identified through critical review of literature and expert's opinion are evaluated with Cronbach's alpha values including item-total correlations or corrected item-total correlations (CITC) using statistical tool. Finally, 20 barriers were analyzed and ranked employing Fuzzy Analytical Hierarchy Process (FAHP).

The study depicts that “Lack of leadership, advisory and monitoring,” “Lack of clarity about economic benefits” and “Lack of integration of LSS with smart tools/I4.0” are potential barriers to drive the path for proper implementation of LSS in Industry 4.0 with due consideration of its technologies in Indian manufacturing industries.

The study provides better knowledge platform for academicians and researchers about hidden aspects of LSS implementation barriers in view of advanced manufacturing technologies. This research will help the practitioners to design their business plans in implementing new quality improvement tools to get advantage in current competitive environment.

The barriers are selected based on literature and opinion from industry and academic experts. Five major criteria are decided after incorporating inputs. The ranking of the barriers is attained by well standard mathematical technique. This will enable the practitioners to design strategies to eliminate the hindrances in order to shape the right path for effective implementation of LSS approach in view of advanced manufacturing technologies.

Organisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this context, drones have the potential to change many industries by making operations more efficient, safer and more economic. Therefore, this study investigates the use of drones as the next step in smart/digital warehouse management to determine their socio-economic benefits.

The study identifies various enablers impacting drone applications to improve inventory management, intra-logistics, inspections and surveillance in smart warehouses through a literature review, a test of concordance and the fuzzy Delphi method. Further, the graph theory matrix approach (GTMA) method was applied to ranking the enablers of drone application in smart/digital warehouses. In the subsequent phase, researchers investigated the relation between the drone application's performance and the enablers of drone adoption using logistic regression analysis under the TOE framework.

This study identifies inventory man agement, intra-logistics, inspections and surveillance are three major applications of drones in the smart warehousing. Further, nine enablers are identified for the adoption of drone in warehouse management. The findings suggest that operational effectiveness, compatibility of drone integration and quality/value offered are the most impactful enablers of drone adoption in warehouses. The logistic regression findings are useful for warehouse managers who are planning to adopt drones in a warehouse for efficient operations.

This study identifies the enablers of drone adoption in the smart and digital warehouse through the literature review and fuzzy Delphi. Therefore, some enablers may be overlooked during the identification process. In addition to this, the analysis is based on the opinion of the expert which might be influenced by their field of expertise.

By considering technology-organisation-environment (TOE) framework warehousing companies identify the opportunities and challenges associated with using drones in a smart warehouse and develop strategies to integrate drones into their operations effectively.

This study proposes a TOE-based framework for the adoption of drones in warehouse management to improve the three prominent warehouse functions inventory management, intra-logistics, inspections and surveillance using the mixed-method.

This study examines academic librarians' perceptions and attitudes toward Internet of Things (IoT) applications in Hong Kong academic libraries and the problems and possible improvements in using IoT technologies to strengthen library services.

This qualitative research used video conferencing software for semi-structured, one-on-one interviews. Participants were given introductory material about the IoT and asked to complete an interview. The data were analyzed using inductive theme clustering for this study.

The analysis identified three themes: perception about applying IoT technology to the library, problems and improvements in using IoT. Participants were generally optimistic about the potential benefits of IoT for improving library operations and providing personalized services. However, they also expressed concerns about privacy and security, errors and extra efforts for information literacy training. They suggested improvements such as incorporating facial recognition technology, advanced RFID technology and collections identification technology to enhance user experience.

Most studies examined users' views rather than librarians' on IoT applications, which few studies cover, especially in East Asia.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

Hospital structures serve to protect and improve public health; however, they are recognized as a major source of environmental degradation. Thus, an effective performance evaluation framework is required to improve hospital sustainability. In this context, this study presents a holistic methodology that integrates the sustainability balanced scorecard (SBSC) with fuzzy Delphi method and fuzzy multi-criteria decision-making approaches for evaluating the sustainability performance of hospitals.

Initially, a comprehensive list of relevant sustainability evaluation criteria was considered based on six SBSC-based dimensions, in line with triple-bottom-line sustainability dimensions, and derived from the literature review and experts’ opinions. Then, the weights of perspectives and their respective criteria are computed and ranked utilizing the fuzzy analytic hierarchy process. Subsequently, the hospitals’ sustainable performance values are ranked based on these criteria using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution.

A numerical application was conducted in six public hospitals to exhibit the proposed model’s applicability. The results of this study revealed that “Patient satisfaction,” “Efficiency,” “Effectiveness,” “Access to care” and “Waste production,” respectively, are the five most important criteria of sustainable performance.

The new model will provide decision-makers with management tools that may help them identify the relevant factors for upgrading the level of sustainability in their hospitals and thus improve public health and community well-being.

This is the first study that proposes a new hybrid decision-making methodology for evaluating and comparing hospitals’ sustainability performance under a fuzzy environment.

The major objectives of this study are to explore the perceptions of library practitioners towards IoT and to suggest directions for its proper application in university libraries of Bangladesh.

The study conducted an online questionnaire-based survey of library practitioners working at university libraries in Bangladesh in addition to an email interview with ten librarians. A sample size of 310 library practitioners was obtained using the convenience sampling technique for the survey. Non-parametric tests were performed to examine the differences in demographics and perspectives on IoT, as well as the potential benefits and challenges of IoT deployment in libraries.

A total of 178 valid surveys were completed, and the results indicate that 147 (82.6%) library practitioners have varied degrees of IoT understanding and positive attitudes about IoT applications in libraries. The study identified RFID, wireless technologies, cloud computing, mobile apps, artificial intelligence and semantic search as major IoT enablers. Tracking, book reservation, circulation, user identification, service marketing, selection of resources, information networking and resource sharing, etc. are the main areas of a library where IoT may be applied. The integration of IoT has the potential to transform conventional libraries into smart libraries. However, there are some challenges that Bangladeshi university libraries must overcome to take use of the prospects emerged from IoT.

The study would encourage Bangladeshi librarians adopting IoT-based library and information services and provide guidelines for its successful implementation.

The study is a pioneering effort from Bangladesh’s perspective which portrays the original opinions and perceptions of library practitioners regarding IoT applications in university libraries of Bangladesh.

Upon completion of the case study, the students will be able to conceptualize the importance of brand differentiation; suggest the implications of brand differentiation in the context of the traditional Chikan art form; examine the aspect of a brand’s product portfolio management; and critically analyse the competitive advantages of the brand using the VRIO framework.

The Chikankari art form gained worldwide recognition. In fact, it also received a geographical indication (GI) tag which is important for international branding. The case is centred around an entrepreneur, Mr. Vinod Punjabi, who redefined the essence of the existing Chikan art form by value addition in terms of intricate designs, patterns and exclusivity. He founded the brand Ada in 2015 aimed at preserving the traditional art form while curating elegance and exclusivity in its product portfolio. The case outlined Punjabi’s journey. The protagonist carefully analysed the open and unorganized Chikankari market and adopted the strategy of brand differentiation to stand apart from the competitors. Punjabi’s daughter, the chief operations officer of Ada, described the aspects. The journey was arduous, but over the years, Ada emerged as a successful name in the Chikankari market. The brand’s intent of becoming synonymous with Chikankari was successful owing to its authentic and exclusive hand-crafted products in the competitive environment of machine-made replicas. Furthermore, the brand also consistently worked on the aesthetic appearance of its store to attract a wide range of customers. Punjabi ensured that the brand was an amalgamation of all the essential elements for its survival in the long run.

The case is aimed for students pursuing bachelor’s and master’s degrees in business administration/diploma in management, marketing and entrepreneurship. Furthermore, it will assist the management trainees in gaining valuable insights.

Teaching notes are available for educators only.

CSS 8: Marketing.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.

The purpose of this study is to investigate the deposition of SS–Al transitional wall using the wire arc directed energy deposition (WA-DED) process with a Cu interlayer. This study also aims to analyse the metallographic properties of the SS–Cu and Al–Cu interfaces and their mechanical properties.

The study used transitional deposition of SS–Al material over each other by incorporating Cu as interlayer between the two. The scanning electron microscope analysis, energy dispersive X-ray analysis, X-ray diffractometer analysis, tensile testing and micro-hardness measurement were performed to investigate the interface characteristics and mechanical properties of the SS–Al transitional wall.

The study discovered that the WA-DED process with a Cu interlayer worked well for the deposition of SS–Al transitional walls. The formation of solid solutions of Fe–Cu and Fe–Si was observed at the SS–Cu interface rather than intermetallic compounds (IMCs), according to the metallographic analysis. On the other hand, three different IMCs were formed at the Al–Cu interface, namely, Al–Cu, Al₂Cu and Al₄Cu₉. The study also observed the formation of a lamellar structure of Al and Al₂Cu at the hypereutectic phase. The mechanical testing revealed that the Al–Cu interface failed without significant deformation, i.e. < 4.73%, indicating the brittleness of the interface.

The study identified the formation of HCP–Fe at the SS–Cu interface, which has not been previously reported in additive manufacturing literature. Furthermore, the study observed the formation of a lamellar structure of Al and Al2Cu phase at the hypereutectic phase, which has not been previously reported in SS–Al transitional wall deposition.

The aim of this study is to empirically investigate the impact of marketing analytics capability on business performance from the perspective of RBV theory.

This study used a survey method to gather information from 225 food processing SMEs registered with the Ghana Enterprise Agency (GEA) in Ghana’s eastern region. A structural equation modeling (SEM) path analysis was used to assess the impact of marketing analytics capability (MAC) on the performance of SMEs.

The results of the study show that MAC significantly and positively affect the financial performance (FP), customer performance (CF), internal business process performance (IBPP) and learning and growth performance (LGP) of Ghanaian SMEs. The findings of this study also illustrated the significance of MAC determinants, including marketing analytics skills (MAS), data resource management (DRM) and data processing capabilities (DPC), in achieving SME success in Ghana.

The research’s conclusions give RBV theory strong credence. The results of this study also provide credence to previous research finding that SMEs should view MAC and its determinants (i.e. DRM, DPC, MAS) as a crucial strategic capability to improve their performance (i.e. FP, CF, IBPP, LGP). With regard to its contribution, this study broadens the body of knowledge on MAC and SME performance, particularly in the context of an emerging economy.