Search results

This research sought to examine the differential effect of chatbot banking artificial intelligence (AI) on consumer experience in the banking industry. A positivist paradigm was adopted to sample 389 consumers who were previously exposed to chatbot banking in Zimbabwe. A causal research design was employed whilst a quantitative approach was followed. In analysing data, the research study applied the structural equation modelling (SEM) technique. The authors found that chatbot banking significantly improves customer experience (CX) in the banking industry. Reliability and responsiveness of the chatbot need to be enhanced for effective improvements in CX. A need was also identified to enhance CX through the development of an ease-to-use chatbot which is embedded in everyday messaging applications of consumers. A significant association was also found between perceived benefits of chatbot banking and CX. This study informs the development of competitive advantage by banks and other related companies through AI-based CX management strategies. In times of pandemics and beyond, chatbot banking can be very instrumental in improving CX.

Introduction: Organisations all over the world are experiencing skill gaps. One of the key factors contributing to the shortage of competent workers is the inability to find candidates that fit the profile. Most of the time, the market does not offer what organisations require.

Purpose: This research focuses on skill shortages and labour market rigidity in the information technology (IT) sector. It discusses the impact of labour shortage and strategies to overcome these challenges.

Need of the Study: The study is required to reduce the skill shortage in the IT sector and inflexibility in the labour market.

Methodology: The data are collected from secondary sources, that is, books, journals and other internet sources.

Findings: The labour market volatility is impacted by several external factors leading to rigidity and talent shortages. Different forecasts within the IT industry, manufacturing, media and telecommunications indicate large-scale labour shortages. The growing influence of digitalisation further creates challenges for organisations during the hiring process as the identified skill gaps for IT professionals are also identified.

Practical Implications: Labour market rigidity affects the labour market. Shifts in labour supply and demand do not always impact wages. Methods are suggested on how to reduce the rigidity in the labour market and, in turn, decrease the skill gaps.

Introduction: Micro, small, and medium enterprises (MSME) have long been viable in the Indian economy. In the case of post-COVID-19, 20–40% of MSMEs in government can be permanently closed. The state should pay special attention to MSMEs for survival (Min, 2023).

Purpose: This chapter provides a framework for MSMEs to study industry challenges in Punjab and to discuss the conceptual framework and road map for future MSMEs in Punjab.

Need for This Study: The COVID-19 pandemic has drastically impacted the variable economic activities within the world. This study is responsible for explaining the different vulnerable sectors related to small- and medium-sized enterprises. On the other hand, this study is an analytical and descriptive research in nature.

Methodology: A mixed method of data collection has been used in this chapter. The data have been collected by floating a questionnaire to the various entrepreneurs of MSMEs. Secondary data have been collected through the Internet.

Findings: Through this research, we could analyse the MSMEs’ conceptual framework, the challenges they face, and the industrial units’ future roadmap.

Practical Implications: This research is mainly considered a clear explanation of current competition and market access challenges that small- and medium-sized enterprises face. This situation is derived due to the COVID-19 pandemic, so many enterprises are trying to find their exit ways. On the other hand, some MSMEs are trying to focus on the online business market to make some profit and to overcome the loss.

The purpose of this study is to look at the factors that drive people to participate in the sharing economy (SE). Based on the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB), the study proposes a mathematical model. The study’s ultimate objective is to help businesses attract more involved customers and promote collaborative consumption as a sustainable alternative to typical consumption patterns. The study offers a conceptual framework established via a thorough literature review to examine Indian customers’ use behavior toward SE platforms. A one-sample two-tailed t-test is used to assess the framework’s efficacy. The research fills gap in the literature on the SE by investigating the factors that determine subjective norms (SN), attitudes (A), and perceived behavioral control (PBC). A framework is provided that takes behavioral intention (BI) contemplated as a mediating variable. The research improves TAM and TPB by including new factors such as technical characteristics. This research adds to the body of knowledge on the digital SE by underlining the relevance of usage behavior in comprehending Indian customers, where A, SN, and PBC are important aspects. The research presents a paradigm for better understanding customers’ attitudes and behaviors toward various SE platforms, which might help academics, practitioners, and policy makers situate their initiatives within the larger field of sharing. The study’s categorizations of Indian consumers’ A, SN, PBC, and BI toward the SE might potentially advise on future research and government policies.