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Sustainability performances (SPs) are the most crucial performances for an organisation in today's world, and they can be measured by economic, social, and environmental metrics. Previous research has not been clear on the role of total productive maintenance (TPM) in the context of sustainability, which motivates the authors to investigate the relationship between TPM and various SPs of the manufacturing firm. Therefore, current research investigates the relationship between TPM and the overall sustainability of the manufacturing firm from the perspective of resource-based view (RBV) theory.

The current study proposed, tested and validated a conceptual framework using partial least squares structural equation modelling (PLS-SEM). A total of 326 responses were received to validate the conceptual framework in smartsPLS 3.0 software.

The research outcomes indicate that TPM considerably impacts a manufacturing firm's economic, environmental and social performance.

This research demonstrates that outstanding shop floor behaviour, such as TPM, can become an important asset to offer competitive advantages in a manufacturing firm. Similarly, TPM might serve as a roadmap for leveraging overall sustainability for manufacturing companies. The study indicates the establishment of a sustainability-oriented training protocol while practising TPM.

No past investigation indicates that a shop floor activity like TPM could be used as an input to offer sustainability in a single index for a manufacturing firm from the perception of RBV theory.

With the advancement of digital transformation, it is important for e-retailers to use artificial intelligence (AI) for customer engagement (CE), as CE enables e-retail brands to succeed. Essentially, AI e-marketing (AIeMktg) is the use of AI technological approaches in e-marketing by blending customer data, and Retail 4.0 is the digitisation of the physical shopping experience. Therefore, in the era of Retail 4.0, this study investigates the factors influencing the use of AIeMktg for transforming CE.

The primary data were collected from 305 e-retailer customers, and the analysis was performed using a quantitative methodology.

The results reveal that AIeMktg has tremendous applications in Retail 4.0 for CE. First, it enables marketers to swiftly and responsibly use data to anticipate and predict customer demands and to provide relevant personalised messages and offers with location-based e-marketing. Second, through a continuous feedback loop, AIeMktg improves offerings by analysing and incorporating insights from a 360-degree view of CE.

The main contribution of this study is to provide theoretical underpinnings of CE, AIeMktg, factors influencing the use of AIeMktg, and customer commitment in the era of Retail 4.0. Subsequently, it builds and validates structural relationships among such theoretical underpinning variables in transforming CE with AIeMktg, which is important for customers to expect a different type of shopping experience across digital channels.

This study aims to identify critical barriers to design thinking (DT) implementation in healthcare and to determine hierarchical relationships among the barriers.

Through an extensive literature review and healthcare experts' opinions, 13 barriers to DT implementation in healthcare were identified. Data were collected using survey questionnaires, and an interpretive structural modeling (ISM) -MICMAC analysis was employed to produce a hierarchical model of identified barriers.

Results reveal the absence of standalone barriers, highlighting “Lack of Organizational autonomy” and “Lack of innovation mindset” as crucial barriers at the bottom of the hierarchy. Overcoming these barriers requires a shift in organizational mindset, dedicated resources, interdisciplinary collaborations, and aligning DT with healthcare regulations.

The findings aid policymakers in recognizing interconnected barriers, enabling DT implementation through strategic mitigation. Healthcare leaders and stakeholders can use this insight to formulate effective strategies for addressing these barriers.

This research presents a distinct investigation of identifying the barriers to DT implementation in the healthcare sector in India. DT’s seamless implementation in hospitals encounters diverse barriers, hindering its full potential. This research contributes to the extant literature by providing the interrelationship between the barriers and a hierarchical model for a clear understanding of the levels of barriers.

Co-creation of services (CCOS) is a collaborative strategy that emphasises customer involvement and their expertise to increase the value of the service experience. In the service ecosystem, artificial intelligence (AI) plays a key role in value co-creation. Therefore, this study is undertaken to empirically uncover how AI can empower CCOS.

The source data were collected from 305 service provider respondents and quantitative methodology was applied for data analysis.

New service development augmented with AI provides tangible value to service providers while also providing intangible value to supportive customers. With AI, service providers adapt to new innovations and enrich additional information, which eventually outperforms human-created services.

AI adoption for CCOS empowerment in service businesses brings “service-market fit”, which represents the significant benefits wherein customers contribute to creativity, intuition, and contextual awareness of services, and AI contributes to large-scale service-related analysis by handling volumes of data, service personalisation, and more time to focus on challenging problems of the market.

This study presents theoretical concepts on AI-empowered CCOS, AI technological innovativeness, customer participation in human-AI interaction, AI-powered customer expertise, and perceived benefits in CCOS, and subsequently discusses the CCOS empowerment framework. Then, it proposes a novel conceptual model based on the theoretical concepts and empirically measures and validates the intention to adopt AI for CCOS empowerment. Overall, the study contributes to novel insight on empowering service co-creation with AI.

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.