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The rise of social media has led to the emergence of influencers and influencer marketing (IM) domains, which have become important areas of academic inquiry. However, despite its prominence as an area for study, several significant challenges must be addressed. One significant challenge involves identifying, assessing and recommending social media influencers (SMIs). This study proposes a semantic network model capable of measuring an influencer's performance on specific topics or subjects to address this issue. This study can assist managers in identifying suitable SMIs based on their estimated reach.

Data from popular YouTube influencers and publicly available performance measures (views and likes) are extracted. Second, the titles of the past videos made by the influencer are used to develop a semantic network connecting all the videos to other videos based on similarity measures. Third, the nearest neighbor approach extracts the neighbors of the target title video. Finally, based on the set of neighbors, a range prediction is made for the views and likes of the target video with the influencer.

The results show that the model can predict an accurate range of views and likes based on the suggested video titles and the content creator, with 69–78% accuracy across different influencers on YouTube.

The current study introduces a novel and innovative approach that exploits the textual association between a SMI's previous content to forecast the outcome of their future content. Although the findings are encouraging, this research recognizes various constraints that upcoming researchers may tackle. Forecasting views of posts concerning novel subjects and precisely adjusting video view counts based on their age constitute two primary limitations of this study.

Managers interested in hiring influencers can employ the suggested approach to evaluate an influencer's potential performance on a specific topic. This research aids managers in making informed decisions regarding influencer selection, utilizing data-based metrics that are simple to comprehend and explain.

The study contributes to outreach evaluation and better estimating the impact of SMIs using a novel semantic network approach.

This paper aims to present a new learning from demonstration-based trajectory planner that generalizes and extracts relevant features of the desired motion for an industrial robot.

The proposed trajectory planner is based on the concept of human arm motion imitation by the robot end-effector. The teleoperation-based real-time control architecture is used for direct and effective imitation learning. Using this architecture, a self-sufficient trajectory planner is designed which has inbuilt mapping strategy and direct learning ability. The proposed approach is also compared with the conventional robot programming approach.

The developed planner was implemented on the 5 degrees-of-freedom industrial robot SCORBOT ER-4u for an object manipulation task. The experimental results revealed that despite morphological differences, the robot imitated the demonstrated trajectory with more than 90 per cent geometric similarity and 60 per cent of the demonstrations were successfully learned by the robot with good positioning accuracy. The proposed planner shows an upper hand over the existing approach in robustness and operational ease.

The approach assumes that the human demonstrator has the requisite expertise of the task demonstration and robot teleoperation. Moreover, the kinematic capabilities and the workspace conditions of the robot are known a priori.

The real-time implementation of the proposed methodology is possible and can be successfully used for industrial automation with very little knowledge of robot programming. The proposed approach reduces the complexities involved in robot programming by direct learning of the task from the demonstration given by the teacher.

This paper discusses a new framework blended with teleoperation and kinematic considerations of the Cartesian space, as well joint space of human and industrial robot and optimization for the robot programming by demonstration.

Given the continuing need to study service marketing adaptations that emerged in the wake of Covid-19, this paper aims to look at the formation and evolution of purchase groups (PGs) that arose in Indian gated communities during the pandemic and have continued functioning in the post-pandemic marketplace. Not only did these groups act as much-needed interstitial markets during a time of significant external disruption, but they also served as sites of value co-creation, with consumers collaborating with each other and with service providers.

Using a phenomenological research approach, the authors conducted 22 in-depth interviews with Indian consumers and small service providers to gather accounts of how PGs started and evolved with time. Subsequent data coding and analyses are conducted with NVivo 12.

Using the service ecosystem perspective, the authors illustrate seven distinct themes that capture the nuances of the formation and evolution of PGs. These consist of entrepreneurality, collectivity, and fluidity at the service ecosystem level, hybridity and transactionality at the servicescape level, and mutuality and permeability at the service encounter level.

This study provides an empirical and theoretically grounded account of a long-term service marketing adaptation that has persisted in the post-pandemic marketplace. This helps us address recent calls for such research while also adding to the work on value co-creation in collective consumption contexts and extant discourse on service ecosystems.

The scope of this study is to explore and summarize the pool of dimensions, models and measurement techniques of service quality used in healthcare services and to propose a comprehensive conceptual model for practitioners and researchers.

This research employs a comprehensive review of available literature by using multiple keywords on different electronic repositories using the recommendations of the PRISMA approach for the selection of articles. A critical analysis of available studies helped in compiling a list of core service quality dimensions in healthcare services.

This paper presents a comprehensive account of different dimensions and their measurement items used by various researchers to assess service quality in healthcare systems. Most of the researchers have used SERVQUAL model either in its original or modified form while the others have proposed and used totally different dimensions to assess the service quality in healthcare. Many dimensions are just an existing dimension of SERVQUAL that has undergone a name change while others are completely new. The dimensions used by many researchers have items drawn from more than one dimension of SERVQUAL model. The availability of so many dimensions and models adds to the confusion that researchers and practicing managers experience when determining the appropriate model to be used in their work. To mitigate this confusion, there is a need to develop a comprehensive model; the current work is an attempt to meet this need. Through our analysis, we identify four major service quality dimensions: clinical quality, infrastructural quality, relationship and managerial quality and propose a model named CIRMQUAL.

After exploring all available models in the domain of healthcare, this research presents the best possible areas to enhance the quality of healthcare services. It also enhances the research insights for academicians and working professionals by developing and proposing a comprehensive model for measuring healthcare service quality. The proposed model covers almost all of the service quality dimensions used by other researchers and will make the choice of dimensions/model easy for the future researchers/practitioners interested in measuring and improving the quality of services offered by their healthcare units. Such a comprehensive model has not been developed by any researcher thus far.

The purpose of this paper is to empirically investigate linkage among productivity, quality, and business performance in home-based brassware units in India.

This study involved action research of home-based brassware units applying procedures for three-stage least-squares (3SLS) regression analysis, with data obtained through questionnaire survey based on convenience sampling.

This study has supported the established belief that quality leads to productivity, and subsequently productivity leads to better business performance for home-based brassware units in India. The consistent and logical result of this study using 3SLS regression analysis has provided empirical understanding of the appropriate linkage among productivity, quality, and business performance.

This study has limitations of findings, as it studied the home-based brassware units in the Indian context only.

This study implies that marketable home-based brassware products are to be produced by taking into account boundaries of production within the framework of goals and value created by motivation and dependability for monitoring the business performance. Identifying an appropriate linkage among productivity, quality, and business performance may project a holistic evaluation of the policy development related to home-based brassware units.

This is an original study to test empirical linkages among productivity, quality, and business performance using 3SLS regression analysis particularly for home-based brassware units in India.

Students’ experiences with instructors and courses determine an institute’s identity. With the instructor analogous to a brand spokesperson and the course to a brand, this study aims to examine the impact of the instructor experiential values on the student’s course experiences, as well as their attitudes and behavioral intentions towards the instructor.

This study uses a mixed-method approach that combines literature review and qualitative research, with two stages of empirical validation using structural equation modeling.

The instructor experiential values comprise appearance, entertainment, escapism, intrinsic enjoyment, efficiency and service excellence. The course experiences are composed of sensory, sentimental, behavioral and intellectual experiences. Strong effects of the instructor experiential values on the course experiences and, in turn, on the students’ attitudes and behavioral intentions are found.

This study contributes to higher education literature by leveraging the theories of meanings transfer, experiential value and brand experience for a unique perspective to the students’ interactions with higher education institute instructors and courses.

The paper’s analogy of an instructor as a brand spokesperson endorsing the course brand is an original contribution to this domain.

Does the simultaneous vertical and horizontal alignment of HR systems positively impact innovation? The authors use the “innovation value chain” model to explore the interplay between the central strategic human resource management concepts of vertical and horizontal fit of HR systems and their role in positively impacting product innovation management.

The authors use the findings from a case study of a large multinational organization in the high-tech sector for the present study. In the first phase, the authors analyse responses to 20 qualitative interviews with senior business and HR executives at the organization using the grounded theory approach. In the second phase, the authors analysed six years of performance ratings and salary data for 4,500–5,500 employees.

Phase 1 of the study established the importance of innovation management as a strategic priority and the role of vertical and horizontal fit of HR systems and practices in positively impacting innovation management. Phase 2 reinforced the findings from Phase 1 by demonstrating the vertical and horizontal fit of the performance and compensation management processes towards furthering innovation management. Our study findings suggest that both forms of fit boost innovation management and interact to reinforce each other mutually, magnifying their respective positive effects towards improving innovation management.

While past studies have generally focused on the isolated role of either the HR system or that of a bundle of HR practices on innovation, the present study empirically demonstrates the simultaneous role of vertical and horizontal fit of HR systems and practices in furthering innovation management. The authors use interviews with senior executives and objective performance and salary data to provide the first experimental evidence of the mechanism of the interplay between the two forms of fit.

The previous researchers have identified human capital, relational capital and structural capital as knowledge assets in knowledge-driven organizations. The current study is an attempt to identify and validate the knowledge assets in construction projects. The study also aims to understand the interrelation of these knowledge assets and their impact on project performance through the development of a conceptual model.

The study is divided into three phases. In phase I, the constructs of “knowledge assets” and “project performance” in construction projects are identified using the exploratory factor analysis. In phase II, these constructs are validated using confirmatory factor analysis. Two separate surveys are conducted for phase I and phase II, respectively. In phase III, the authors develop two conceptual models based on the literature review and two construction project cases in India. The models examine the inter-relationship of knowledge assets and measures their impact on project performance. The models are empirically tested using the responses of the second survey through a structural equation model.

The study extracts four knowledge asset constructs and one performance construct which are named human capital, structural capital, relational capital, human capital capacity building process and project performance, respectively. The study finds that both the conceptual models are statistically excellent fit. The results of the models suggest that relational capital and structural capital have a direct positive impact on project performance, whereas human capital has an indirect effect on project performance mediated through relational capital, structural capital and human capital capacity building process.

The items for knowledge asset constructs and measurement of project performance are moderated by experts, working in construction projects in India, hence the process may contain subjective bias. Further, two construction project cases were selected by authors in the study that originate from India.

The study has implications for the project executors (contractors) as well as for project owners. The contractors must maintain healthy relations with all the stakeholders in a project like a client, suppliers, architects, etc. They must develop systems that are people-friendly to avoid the problems of time and cost overruns in projects. The owners must also maintain healthy relations. This can result in a win-win situation for both parties and can lead to superior project performance.

The study develops and empirically tests two conceptual models that explain the interrelations of knowledge assets and how it benefits the construction project performance in India. Therefore, the generalization of the results is difficult; however, the results can be replicated in projects with similar settings.

Digital transformation (DT) and supply chain resilience have received increasing attention. Structural social capital (SSC) and human capital (HC) have recently been identified as strategic resources for small and medium-sized enterprises (SMEs). While the significant role of entrepreneurial competencies (ECs), SME innovativeness (SMI) and technology adoption (TA) in driving business performance have been partially researched, no studies have simultaneously examined the effect of these resources and capabilities on SME business performance growth (BPG) under the lenses of a resource-based view (RBV) and dynamic capabilities (DCs) as well as in the context of DT. This study aims to clarify these unclear relationships.

This study adopts established theoretical lenses, a mixed-methods approach and structural equation modeling (SEM) using a sample of 371 respondents who are top and middle SME managers in Vietnam.

The study discovers the significant and insignificant relationships between HC, SSC, ECs, SMI, TA and BPG besides providing a new measurement and reconciling existing measurements for the DT context. Some implications for driving SMEs' DT are also suggested.

This study is the first to thoroughly examine the effect of HC and SSC on SMEs' BPG through the mediating role of ECs, SMI and TA under RBV and DCs lenses in the DT context. The investigation is conducted in an emerging market, where DT implementation is in the process of being learned and experimented upon.