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This study aims to design a facility network for the weavers to do direct business in the Indian handloom industry by using tourists as potential customers.

Data from 4,001 weavers of the handloom industry and 82 tourist locations of Varanasi city were collected. This data was analysed using the k-mean and elbow methods to determine the locations and the optimal number of collection centres, selling stores and warehouses to provide opportunities for the weavers to do direct business.

The study's findings showed that a greater opportunity could be provided with four optimal collection centres and selling stores, along with two warehouses in the handloom industry of Varanasi city. These results provide valuable guidance for policymakers to plan the Varanasi handloom network of facilities efficiently and effectively to improve the conditions of weavers.

Determining the optimal locations is crucial for designing a facility network. The proposed network will aid the government and policymakers in comprehending and pinpointing potential sites to establish new facilities in the handloom industry in Varanasi, a city with tourism potential.

Online grocery service (OGS) has significantly grown in recent years, particularly during the Covid-19 pandemic. This surge has attracted significant scholarly attention and resulted in many scientific articles in the last five years. Adopting a bibliometric review approach, this study attempts to comprehensively and systematically analyse the academic literature on OGS.

A Scopus search using pertinent keywords followed by PRISMA screening identified 384 relevant articles. Articles were analysed using VOSviewer and Biblioshiny, which employed citation and thematic analysis.

The study identifies the significantly impactful authors, articles, and journals. While the analysis reveals the evolution across four time-frames, it also highlights the clusters representing the literature strands. Six major themes are identified in the literature, and potential future research enquiries are suggested.

As the first study to include over 350 articles, it comprehensively represents the current state of the OGS literature, utilising performance and thematic analysis techniques. The article contributes significantly to the academic discourse surrounding OGS by synthesising and presenting diverse themes. Further, the future research questions provide a foundation for advancing the literature and guiding future scholarly work in the OGS domain.

The study aims to provide insights in the sensemaking process and the use of business analytics (BA) for project selection and prioritisation in start-up settings. A major focus is on the various ways start-ups can understand their data through the analytical process of sensemaking.

This is a comparative case study of two start-ups that use BA in their projects. The authors follow an interpretive approach and draw from the constructivist grounded theory method (GTM) for the purpose of data analysis, whereby the theory of sensemaking functions as the sensitising device that supports the interpretation of the data.

The key findings lie within the scope of project selection and prioritisation, where the sensemaking process is implicitly influenced by each start-up's strategy and business model. BA helps start-ups notice changes within their internal and external environment and focus their attention on the more critical questions along the lines of their processes, operations and business model. However, BA alone cannot support decision-making around less structured problems such as project selection and prioritisation, where intuitive judgement and personal opinion are still heavily used.

This study extends the research on BA applied in organisations as tools for business development. Specifically, the authors draw on the literature of BA tools in support of project management from multiple perspectives. The perspectives include but are not limited to project assessment and prioritisation. The authors view the decision-making process and the path from insight to value, as a sensemaking process, where data become part of the sensemaking roadmap and BA helps start-ups navigate the decision-making process.

Designing effective business analytics (BA) platforms that visualise data, provide deep insights and support data-driven decision-making is a challenging task. Understanding the elements shaping BA platform design is crucial for success. The purpose of this study is to explore the impact of visualisation on usability (UI) and user experience (UX) while emphasising the importance of insights understanding in BA platform design.

This paper presents a case study following a startup’s journey as it undergoes two redesign phases for its BA platform. A combination of quantitative and qualitative methods is used to assess UX/UI and insights understanding of the platform. Indicatively this included semi-structured interviews, observations, think-aloud techniques and surveys to monitor runtime per task, number of errors, users’ emotions and users’ understanding.

Our findings suggest that modifications in aesthetics and information visualisation positively influence overall usability, UX, and understanding of platform insights – a critical aspect for the success of the startup.

Our goal is not to make a methodological contribution, but to illustrate how companies, constrained by time and pressure, navigate platform changes without meticulous design and provide learnings on important elements while designing BA platforms.

This paper concludes with suggested methods for assessing BA platforms and recommends practical practices to follow. These practices include recommendations on important elements for BA platform users, such as navigation and interactivity, user control and personalisation, visual consistency and effective visualisation.

This study contributes to practice as it presents a real-life case and offers valuable insights for practitioners.

Performance management system (PMS) is a crucial element of strategic human resource practices in any organization. This research aims to provide a concise overview of how bibliometric analysis is employed to assess the influence and significance of cutting-edge technologies in shaping of PMS. This study seeks to identify key trends, emerging technologies and their impact on the evolution of performance management practices, contributing valuable insights for researchers, practitioners and policymakers in this field.

This investigation is carried out utilizing total of eight research questions, which are examined through VOS Viewer and Biblioshiny software. The research offers visual diagrams and tables depicting the data extracted from the Scopus Database.

The study’s results underscore a noticeable increase in research literature pertaining to PMS, indicating a shift from conventional methods to a strategic, technology-driven approach. These findings cover the way for further investigation across various disciplines, offering opportunities to enhance the efficacy and productivity of PMS.

The implementation of new technologies such as Artificial intelligence (AI), machine learning and robotics etc. in PMS have also been analysed to give a sneak peak of the bigger future picture of AI and strategic human resource integration.

To the best of the authors' understanding, this analysis represents the inaugural application of bibliometric techniques to evaluate the advancement of research on Performance Management System (PMS) dating back to 1978, utilizing academic literature sourced from the Scopus database.

The primary purpose of this study is to examine the relationship between conumers' emotional attachment towards fashion apps and positive behavioral outcomes, such as e-WoM and repurchase intention. The study also aims to explore how e-servicescape, customer experience and perceived value of online shopping influence this relationships.

The study has used quantitative research methods to collect data from a sample of 484 consumers who had previous experience of purchasing using fashion apps. Data were collected from university students enrolled in university in Gujarat, India using an online self-administered questionnaire. The data are analyzed using structure equation modeling to determine the relationships between the variables under investigation.

The results demonstrate relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM. The study found support for hypotheses 1, 2 and 3, highlighting the influence of e-servicescape, customer experience and perceived value of online shopping in developing emotional attachment with fashion apps. The study also confirmed hypotheses 5 and 6, which suggest that consumers who have a stronger emotional attachment to fashion apps are more likely to intend to repurchase fashion products and engage in positive electronic word-of-mouth behavior for fashion brands.

In today's digital age, fashion apps are vital for fashion retailers to remain competitive and offer their customers a smooth and immersive shopping experience . Given the potential impact of fashion apps on the customer behavior, it is essential to investigate the relationship relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM in the context of fashion apps. The findings of the study are expected to contribute to the understanding of consumer behavior in the context of fashion apps and e-commerce more broadly. The results may also provide insights into how fashion retailers can improve their online presence and customer experiences to increase emotional attachment and positive behavioral outcomes.

The results of this study have several implications for online retail managers and fashion app developers. The study provides strong support for the idea that the extent to which online customers feel emotionally attached to fashion apps is strongly related to their e-WoM and repurchase intention. Moreover, the results of the study suggest that online retailers who are looking to cultivate emotional connections with consumers through fashion apps should prioritize three key areas: e-servicescape, customer experience and perceived value of online shopping.

The purpose of this paper is to provide a systematic review of literature on corporate engagement with start-ups (CEWS) by identifying the modes, contexts, antecedents, barriers and outcomes. As an emerging field, CEWS presently has no such review available which will help in building consensus within the field and shape future research directions.

The study followed a two-phased systematic review of literature. Three research databases (i.e. Web of Science, ScienceDirect and SCOPUS) were accessed to gather and conduct the review. Of the total 379 papers retrieved, 63 total relevant papers were studied and analysed. The exhaustive review of literature helped to uncover the contexts, perspectives, antecedents, outcomes and barriers reported across the different modes of CEWS.

The study highlighted the five prominent modes of CEWS favoured by large corporations and start-ups. It found that the large corporations and start-ups associate with one another on the basis of complementarities of activities, resources and motives to pursue their strategic orientations. The engagements also face barriers on the ground, such as incompatibility of goals, power imbalances, cultural differences and weak engagement plans. Most important contexts seen were the high-technology industries in the developed economies like the USA and Europe. It also found that ecosystem creation, accessing innovation and corporate strategy have been preferred as the most productive modes of CEWS in the literature.

This review provides practitioners with a detailed list of the modes and drivers of CEWS. Subsequently, the barriers that need to be managed to successfully execute a specific mode of engagement. This shall enable the practitioners in developing and adopting the best practices while engaging with the start-ups to better facilitate the outcomes of CEWS.

To the best of the authors’ knowledge, there is no systematic literature review available in the domain of CEWS – thus, this study makes an important methodological contribution to the field. By consolidating the fragmented yet growing knowledge on CEWS, the study presents a detailed understanding of what drives and obstructs the engagement between large corporations and start-ups.

The purpose of the quantitative correlational research study was to determine the relationship, if any, between the predictor variable, cosmeceutical business service quality, and the outcome variable, cosmeceutical client satisfaction, in the southeast region of the United States of America. Cosmeceuticals were cosmetics and medications administered by estheticians.

Literature on business service quality and client satisfaction theories was synthesized after extensive review. Quantitative research data were collected and statistically analyzed on the following subscales of consumer satisfaction: general satisfaction, technical quality, interpersonal manner, communication, financial aspects, time spent with professionals and accessibility/convenience. The hypotheses addressed the research question (RQ) of whether cosmeceutical business service quality affects client satisfaction. The Cosmeceutical Client Satisfaction Questionnaire 18 (CCSQ-18), a web-based research instrument, had strong reliability with a Cronbach’s alpha of 0.84. The target population (N = 50) included randomly selected female cosmeceutical consumers in the southeast region of the United States of America. The researcher did not digress from the detailed research protocol, instrumentation, data collection or data analyses. Through the Likelihood Ratio (LR) chi-squared statistic (18) = 65.35 and its associated probability, Prob > chi-squared = 0.000, the researcher determined the predictor variable cohesively has a statistically significant effect on the outcome variable.

Research results concluded that a significant relationship exists between cosmeceutical business service quality and cosmeceutical client satisfaction in the southeast region of the United States of America.

The findings detailed in the results complimented the argument that, generally, business service quality is important to consider, because good business is based on client satisfaction.

Despite the enormous benefits, smart homes (SHs) are still not widely adopted by residents in China. Furthermore, research on the intention to use SHs has overlooked the role of family factors. Thus, this study aims to propose a new research model to examine the impact of family factors on the usage intention (UI) of SHs.

This study collected 265 valid data from potential users of SHs in China using a convenience sampling method. The PLS-SEM method was applied to test the research model and related hypotheses.

The empirical results confirm the mediating role of optimism (OP) in perceived family support (PFS)/perceived family trust (PFT) and attitude (AT). Unsurprisingly, the results validated the relationship between perceived usefulness (PU), attitude (AT) and UI of SHs through TAM theory. Besides, this study also identified the moderating effect of perceived risk (PR) between AT and UI.

To improve SH adoption, practitioners should focus on family factors and utilize family influence to promote the spread of smart home reputation. Besides, SH practitioners should enhance user trust and reduce perceived risks through technological upgrades and security measures.

Based on the Social Impact Theory and Technology Acceptance Model (TAM), this study is an empirical attempt to explore the impact of family factors on the intention to use SHs, expanding the research on smart home adoption.

Advances in technology have given rise to an increased demand by small businesses for personalised e-government services. Given the importance of small businesses to the Australian economy, it is vital to deliver small business-centric services that offer potential to generate value. To do that effectively, government departments need to understand factors that affect small business. The purpose of this study is to explore how preferences for personalised services and the use of intermediaries affect small business participation behaviour and, in turn, stimulate positive outcomes that are of interest to the government.

This study draws on secondary data from a survey of 800 Australian small businesses about the digital services offered by a large government department. Structural equation modelling was used to empirically test the model.

The findings demonstrate that whilst preference for personalisation has a positive relationship with participation behaviour, reliance on an intermediary does not. While such behaviour fosters emotional connection and perceptions of partner quality, the results of this study show no significant impact on satisfaction.

This study advances knowledge about how small businesses can gain value from personalised support services. Importantly, it focuses on participation behaviour and small business – both of which are largely absent from existing studies. The findings can assist government departments to design personalised services that are valued by small businesses.