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The advent of robotics and automation technologies was augmenting firm initiatives to attain competitive advantage. From a resource-based view perspective, human-led capabilities were important to operate with technology resource base of an organisation. This was evident for both manufacturing as well as services firms. However, employees as an individual confronted technology anxiety (TA) when they were working with new technologies like robotics and automation technologies. Thus, the purpose of this paper was to examine the factors causing TA.

Given the novelty of this research study context a qualitative exploratory method was designed. For this research study, the data collected was through in-depth interviews conducted through open-ended semi-structured questionnaire. The data was collected from 62 frontline employees who were working with robotics and automation-based technologies in manufacturing firms. The authors applied thematic content analysis on collected data for analysis.

Technology anxieties ranged from fear of complete inability to learn new technologies, failure to learn new technologies properly, incapability to implement the learned skills and job loss to younger technology savvy employees. Finally, there was anxiety over job loss as automation and robotic technologies over the years was expected to erode the employment of human workforce altogether.

The author undertook the research study based upon the TA perspective advocated by Meuter et al. (2003) and Yang and Forney (2013). Furthermore, this research study in the context of robotics and automation-based technologies in the manufacturing sector applied the mental accounting theory (Thaler, 1999) and technology self-efficacy perspective (Huffman et al., 2013).

Managers involved in the implementation of robotics and automation-based technologies were required to address TA of employees. Fear of job loss had to be addressed specially in a country like India. Anxiety regarding the ability to learn to work with robotics and automation technologies also was needed to be addressed by managers through adequate training and time for preparation. The benefits of robotics and automation-based technologies for employees as well as organisations have to be ascertained through open communication between the management and the frontline employees.

To the best of the authors’ knowledge, this was one of the first empirical research studies which deliberated regarding TA in the context of frontline workers working with robotics and automation-based technologies in the manufacturing sector. This research study was based upon a combination of varied perspectives ranging from micro foundations theory, TA, mental accounting theory and technology self-efficacy perspective.

The purpose of this study was to investigate potential direct impact of environmental, social and governance factors (ESG) on organisational innovation and their role as isomorphic factors in multinational life sciences organisations.

The authors applied necessary condition analysis (NCA), using the R statistical tool to determine the direct impact of environmental (E), social (S), governance(G) and composite ESG factors on innovation, represented by research and development (R&D) expenditure across a sample of 86 multinational life sciences companies.

The study established that ESG factors have a positive impact on the innovation output of multinational firms in the life sciences industry. Further, the study also established that ESG factors act as isomorphic factors in the organisation of multinational life sciences firms in implementing sustainability practices.

This empirical research study was a novel attempt to establish a direct impact of ESG factors on innovation output of multinational life sciences firms. This was one of the first empirical studies to integrate the institutional theory with the resource-based view and thereby demonstrate that ESG factors had a significant role in contributing to institutional isomorphic behaviour, in the form of sustainable innovation as a strategy. This study established the importance of ESG factors in defining the sustainability agenda of multinational life sciences organisations. Lastly, the study elucidates the benefits of the integration of sustainability as a strategy in multinational life sciences corporations.

The purpose of this study was to comprehend the adoption of artificial intelligence (AI) technology-driven natural large language model (LLM)-based chatbots by customers.

A qualitative research study method was conducted. This was to explore managerial perspectives towards consumer centric technology adoption of AI plus LLM-based chatbots. This was specifically for AI-driven natural LLM-based chatbots services. The author conducted conducted in-depth personal interviews with 32 experts of digital content AI + LLM chatbot services. Thematic content analysis was undertaken to analyse the data.

The advent of natural language processing tools driven by AI technology chatbots has altered human-firm interaction. The research findings indicated that the push-pull-mooring (PPM) factors captured the phenomenon in the most comprehensive way. A total of 15 key factors influencing the adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction were identified in this study by the author. The thematic content analysis unraveled insights regarding transformed consumer adoptions towards AI-driven LLM-based chatbots by means of the PPM framework factors.

The empirical research investigation contributed to the literature on the PPM theoretical framework. This was specifically in the context of adoption of AI technology-driven natural LLM-based chatbots by customers during firm customer interaction.

The research study insights would help managers to restructure and reconfigure their organizational processes. This would neccessiated a shift in firm-customer interactions as demanded because of the availability of AI technology-driven natural LLM-based chatbots by customers.

This research study was based upon the PPM theoretical framework. This study provided a unique analysis of the altered firm customer interaction needs and requirements. This was one of the first studies that applied the framework of PPM theory regarding the adoption of AI technology-driven natural LLM-based chatbots by customers.

The purpose of this study is to examine the factors that drive superior social enterprise performance for women-led social enterprises. The authors examined the role of individual entrepreneur cognitive characteristics contributing to social enterprise performance and recommended a framework for women's social entrepreneur development.

The authors conducted an exploratory qualitative study of 22 women founders of social enterprises using a semi-structured questionnaire. In-depth interviews were conducted, and the transcripts were analyzed using thematic content analysis.

This study found a significant impact of self-efficacy on the performance of social enterprises among the studied subjects. Social support in the form of material, information and emotional support enhanced the ability of women social entrepreneurs to better achieve business sustenance and continuance of operations. The business skills of the women social entrepreneurs led them to move from just social impact generators to becoming thought leaders. The strong prosocial motivation of the founders contributed to building their resilience in the face of adversity.

This study extended the existing theories on social entrepreneurship by bringing the dimensions of entrepreneurial resilience in driving social enterprise performance along with business skills. Thus, it provided an enhanced explanation to the existing body of knowledge on contributors to superior social enterprise performance.

This study gathered insights into the role of entrepreneurship education focused on business skills, especially for women social entrepreneurs in achieving superior performance for their social ventures. This also reconfirmed the role of social support and how structurally this could be provided by educational systems to aspiring women social entrepreneurs.

The practice of social entrepreneurship by women social entrepreneurs has been growing. Its importance in developing economies because of its ability to make grassroots changes at the lower levels of society was substantive. Women have shown more inclination toward social business with an affinity for prosocial contribution. By focusing on nurturing these social enterprises, governments as well as global agencies like the United Nations and the World Economic Forum could accelerate social change. Furthermore, support for the current women social entrepreneurs as change-makers making a difference in society could be achieved.

To the best of the authors’ knowledge, this research study was one of the first studies on women social entrepreneurs focusing on the factors of self-efficacy, social support and entrepreneurial resilience contributing to social enterprise performance. This study combined the social entrepreneurship intention theory with entrepreneurial resilience and business skills to understand the factors leading to successful social enterprise performance for women social entrepreneurs.

The purpose of this study is to explore the complex interplay between technology, personal norms and emotional factors in shaping the sustainable housing choices of millennials in emerging economies. It integrates the model of goal-directed behavior, technology acceptance model and norm activation model, incorporating both self-interest and prosocial motivations. Key adaptations involve replacing perceived behavioral control with financial self-efficacy and substituting hedonic motivation for anticipated positive emotions. Moreover, it introduces location as a practical anchor.

A quantitative, cross-sectional and descriptive research design was used in this study. Data were gathered from a sample of 610 millennial residential real estate investors across Indian smart cities. A multistage stratified sampling technique was used to ensure a representative sample. For data analysis, partial least squares structural equation modeling was used. The analysis focused on hypothesis testing to examine the relationships between the constructs of interest. Bootstrap t-values and effect sizes were used to assess the significance and magnitude of these relationships, respectively.

One of the key findings of this study was the establishment of significant positive relationships between awareness of consequences, ascription of responsibility and personal norms with behavioral intentions. This underscored the importance of personal ethical considerations in shaping intentions. Perceived usefulness and ease of use were found to significantly influence attitudes positively, highlighting the relevance of these factors in forming favorable attitudes toward behaviors. Attitude, subjective norms, financial self-efficacy and location played significant positive roles. However, negative anticipated emotions decreased desire. This illustrated the complex role emotions play in motivational processes. The study also revealed that subjective norms did not significantly contribute to shaping personal norms. This indicated a potential decoupling of societal expectations from personal ethical obligations in the decision-making process.

This study offers actionable insights for both policymakers and real estate developers. For policymakers, the findings highlight the need to craft initiatives that go beyond mere awareness, instead fostering a deep sense of personal responsibility and environmental stewardship among potential homebuyers. For real estate developers, the emphasis on financial self-efficacy and location suggests a strategy shift toward designing sustainable homes that not only meet environmental standards but also align with buyers’ financial confidence and geographic preferences. Together, these strategies can drive a more widespread adoption of sustainable housing, making sustainability a tangible and appealing choice for millennials.

To the best of the authors’ knowledge, this empirical research study was one of the first studies that contributed to the literature by integrating the model of goal-directed behavior, technology acceptance model and norm activation model. This study thus offered a nuanced understanding of the interplay between normative influences, usability perceptions, ethical considerations and emotions in the context of behavioral intentions.

The purpose of this research was to study sustainable water resource management using a stimulus-organism-response (SOR) perspective.

This research study was an exploratory qualitative study. Thematic content analysis was used based on semi-structured interviews with 30 experts operating in the USA, representing 26 water-intensive organisations across different industries. The study was anchored in the theoretical foundations of SOR perspectives.

The results of this study revealed several fundamental factors, processes and forces that were considered by organisations for sustainable water resource management. Managers evaluated risks relative to water resources and developed strategic initiatives regarding water management. The authors found that often organisations considered water resources management aspects while deciding business operations. This was especially true for substantive water resource-consuming organisations with wide geographical operations.

Through this study, the authors explained how the interrelationship between organisations and water resources presented risks and challenges. The authors applied SOR theoretical perspective in this research study. This was while factoring in an organisation’s present considerations and future plans regarding sustainable water resource management. Thus, the study findings were expected to further interdisciplinary research at the intersection of organisational and environmental studies.

The finding that water sustainability challenges and efforts could act as strong motivating forces for innovation and technology was significant. Water sustainability challenges could also be a catalyst for synergistic collaborations amongst organisations and diverse groups of institutions. The study insights were relevant to organisational scholars, the water management industry regulators and managers involved with organisational sustainability programmes.

Organisational challenges regarding sustainable water resource management have been influenced by growing populations and climate change. Furthermore, the increasing context of scarcity was compounded by increased pressures from numerous stakeholders. Although critical water management issues were recognised by organisations, relatively little was known about how organisational managers were planning for and responding to these issues. This research study contributed towards addressing the mentioned research gap.

The purpose of this study is to understand the investment decision-making of real estate investors in housing, highlighting the interplay between rational and irrational factors. In this study, investment satisfaction was a mediator, while reinvestment intention was the dependent variable.

A quantitative, cross-sectional and descriptive research design was used, gathering data from a sample of 550 residential real estate investors using a multi-stage stratified sampling technique. The partial least squares structural equation modelling disjoint two-stage approach was used for data analysis. This methodological approach allowed for an in-depth examination of the relationship between rational factors such as location, profitability, financial viability, environmental considerations and legal aspects alongside irrational factors including various biases like overconfidence, availability, anchoring, representative and information cascade.

This study strongly supports the adaptive market hypothesis, showing that residential real estate investor behaviour is dynamic, combining rational and irrational elements influenced by evolutionary psychology. This challenges traditional views of investment decision-making. It also establishes that behavioural biases, key to adapting to market changes, are crucial in shaping residential property market efficiency. Essentially, the study uncovers an evolving real estate investment landscape driven by evolutionary behavioural patterns.

This research redefines rationality in behavioural finance by illustrating psychological biases as adaptive tools within the residential property market, urging a holistic integration of these insights into real estate investment theories.

The study reshapes property valuation models by blending economic and psychological perspectives, enhancing investor understanding and market efficiency. These interdisciplinary insights offer a blueprint for improved regulatory policies, investor education and targeted real estate marketing, fundamentally transforming the sector’s dynamics.

Unlike previous studies, the research uniquely integrates human cognitive behaviour theories from psychology and business studies, specifically in the context of residential property investment. This interdisciplinary approach offers a more nuanced understanding of investor behaviour.

This research study aims to inquire into the technostress phenomenon at an organizational level from machine learning (ML) and artificial intelligence (AI) deployment. The authors investigated the role of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management amongst managers.

The authors applied an exploratory qualitative method and conducted in-depth interviews based on a semi-structured interview questionnaire. Data were collected from 26 subject matter experts. The data transcripts were analyzed using thematic content analysis.

The study results indicated that role ambiguity, job insecurity and the technology environment contributed to technostress because of ML and AI technologies deployment. Complexity, uncertainty, reliability and usefulness were primary technology environment-related stress. The novel integration of ML and AI automation-augmentation interdependence, along with socio-technical systems, could be effectively used for technostress management at the organizational level.

This research study contributed to theoretical discourse regarding the technostress in organizations because of increased ML and AI technologies deployment. This study identified the main techno stressors and contributed critical and novel insights regarding the theorization of coping mechanisms for technostress management in organizations from ML and AI deployment.

The phenomenon of technostress because of ML and AI technologies could have restricting effects on organizational performance. Executives could follow the simultaneous deployment of ML and AI technologies-based automation-augmentation strategy along with socio-technical measures to cope with technostress. Managers could support the technical up-skilling of employees, the realization of ML and AI value, the implementation of technology-driven change management and strategic planning of ML and AI technologies deployment.

This research study was among the first few studies providing critical insights regarding the technostress at the organizational level because of ML and AI deployment. This research study integrated the novel theoretical paradigm of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management.

The purpose of this study is to identify the factors that contribute to the successful implementation and management of sustainable innovation in research-intensive sectors such as the life sciences industry.

The study was conducted through a combination of two methods. The first was qualitative interviews of 21 sustainability experts and leaders in the life sciences industry who were responsible for implementing sustainable innovation. They were selected through nonprobabilistic purposive sampling. The second method was thematic content analysis using the MAXQDA software.

The study identified that successful implementation of sustainable innovation in research-intensive firms begins with the alignment of the executive vision for sustainability with the business objectives of the research-intensive firm. Furthermore, implementation of sustainability practices is identified as a function of organizational reconfigurations that facilitate purposeful inflow and outflow of ideas and knowledge between internal firm resources and external stakeholders, anchored by the objectives of the research-intensive firm.

The study explicated factors only within life sciences industry based on qualitative interviews. The study offers scope for cross-sector quantitative evaluation.

To the best of the authors’ knowledge, this study is among the first studies to systematically delineate the underlying factors that govern successful implementation of sustainable innovation in research-intensive industries, through integration of the resource-based view and stakeholder theory and thereby provide a framework for research-intensive organizations to implement sustainable innovation practices.

In this study, we investigated the positive and negative effects of stress that is driven by responsible artificial intelligence (RAI) principles on employee job outcomes by adapting the challenge–hindrance stressors model.

The study design involved empirically validating the proposed model on 299 respondents who use AI for work-related tasks.

The results revealed several RAI-driven challenge and hindrance stressors related to employees’ positive and negative psychological responses and task performance in a digital workplace. Practitioners could use the RAI characteristics to improve employees’ RAI-driven task performance.

This study contributes to the ongoing discussion on technostress and awareness in the context of RAI in the AI literature. By extending the C-HS model to the RAI context, it complements the context-specific technostress literature by conceptualizing different characteristics of RAI as RAI-driven stressors.

Adoption and use of technologies like RAI are not automatically translated into expected job outcomes. Instead, practitioners and academicians also need to know whether the RAI characteristics actually help employees show positive or negative behavior. Furthermore, relying on the challenge–hindrance stressor (C-HS) model, we try to reveal the beneficial and detrimental effects of different RAI characteristics on employees’ job outcomes.