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The purpose of this study is to assess how intergovernmental panel on climate change’s (IPCC’s) sixth assessment report of Working Group I (WGI), a Summary for Policymakers (SPM), has evaluated the current climate change situation. The author uses the qualitative content analysis (QCA) method (i.e. summative content analysis [SCA]) to identify critical points of the SPM.

To better understand the WGI report and its SPM, the author uses the thematic analysis, often called the QCA method. This study takes more steps and uses one of the main qualitative content analysis approaches (i.e. SCA). Therefore, QCA (SCA) can help the author count the occurrence of certain words using computer-assisted qualitative data analysis software that quantifies the words in the data. This process helps the author to understand codes and patterns (e.g. the concept in the results section).

Interestingly, the AR6 says more about adaptation for policy makers in sections C (Climate information for risk assessment) and D (Mitigation of future climate change) than in sections A and D. Finally, this study concludes that the IPCC WGI SPM has addressed evidence on global climate change policymaking for SPMa, SPMd (mitigation-based strategies and mitigation policy [MP]) and SPMb, SPMc (adaptation policy and adaptation-based strategy).

First, this study refers only to the contribution of WGI, a SPM. The findings of this study do not necessarily provide a full understanding of what the AR6 WGI SPM says about climate change. It points out that the QDA Miner software and Voyant tool do not include all variables and examples where mitigation and adaptation-based strategies are discussed. The guidance for coding is based on the approved version of IPCC AR6 WGI SPM. The final limitation is that the relatedness of key words (e.g. confidence, high and warming) is sometimes ambiguous; even experts may disagree on how the words are linked to form a concept. Thus, this method works at the keyword level. A more intelligent method would use more meaningful information than keywords.

This study used qualitative data analysis (SCA) to explore what was said about climate change in four sections of the IPCC AR6 WGI SPM, which may influence current and future global climate change policymaking.

This study aims to investigate how art events can enrich novice visitors by transforming their practices.

This research uses an interpretive case study of the art exhibition “1/1/1/1/1” in the Oppenheim gallery in Wroclaw. It draws on multiple sources of evidence, namely, novice visitors’ interviews, observation including photo studies and content analysis of art-makers’ mediation sources. This study is an example of contextual theorizing from case studies and participatory action research with researchers as change agents.

The evidence highlights that aesthetic values and experiences are contextual to practices and are transformable into other values. The findings illustrate the role of practice theory in studying how art-makers inspire the transformation of practices, including values driving the latter.

The findings provide implications for transformations of co-creating contextual values in contemporary visual art consumption and customer experience management.

Practical implications to arts organizations are also provided regarding cultural mediation conducted by art-makers. Exhibition makers should explain the meanings of the particularly visible artefacts to allow visitors to develop a congruent understanding of the meanings. The explanations should not provide ready answers or solutions to the problem art-makers suggest to rethink.

The social implication of our findings is that stakeholders in artistic ventures may undertake adequate, qualified and convergent actions to maintain or transform the defined interactive practices between them in co-creating contextual aesthetic values.

The study provides new insights into co-creating values in practices in the domain of contemporary art exhibitions by bringing the practice theory together with an audience enrichment category, thus illustrating how novice visitors get enriched by transforming their practices led by contextual values of “liking” and “understanding”.

The impact of frontline robots (FLRs) on customer orientation perceptions remains unclear. This is remarkable because customers may associate FLRs with standardization and cost-cutting, such that they may not fit firms that aim to be customer oriented.

In four experiments, data are collected from customers interacting with frontline employees (FLEs) and FLRs in different settings.

FLEs are perceived as more customer-oriented than FLRs due to higher competence and warmth evaluations. A relational interaction style attenuates the difference in perceived competence between FLRs and FLEs. These agents are also perceived as more similar in competence and warmth when FLRs participate in the customer journey's information and negotiation stages. Switching from FLE to FLR in the journey harms FLR evaluations.

The authors recommend firms to place FLRs only in the negotiation stage or in both the information and negotiation stages of the customer journey. Still then customers should not transition from employees to robots (vice versa does no harm). Firms should ensure that FLRs utilize a relational style when interacting with customers for optimal effects.

The authors bridge the FLR and sales/marketing literature by drawing on social cognition theory. The authors also identify the product categories for which customers are willing to negotiate with an FLR. Broadly speaking, this study’s findings underline that customers perceive robots as having agency (i.e. the mental capacity for acting with intentionality) and, just as humans, can be customer-oriented.

This paper aims to investigate the impact of Industry 4.0 (I4.0) technologies on knowledge creation for innovation purposes by assessing the relationships among the variety of I4.0 technologies adopted (breadth I4.0), the penetration of these technologies within the firm’s value chain activities (depth I4.0) and the mediating role of both internal (inter-functional (IF)) and external [with knowledge-intensive business services (KIBS)] collaborations in this process.

The study employed a quantitative research design. By administering a survey to entrepreneurs, chief operation officers or managers in charge of the operational and technological processes of Italian manufacturing firms, the authors collected 137 useful questionnaires. To test this study's theoretical framework and hypotheses, the authors ran regression and mediation analyses.

First, the results highlight the positive link between breadth I4.0 and depth I4.0. Moreover, the results show the key role played by increased collaboration among the firm’s business functions and by relationships with KIBS in creating knowledge to innovate processes and products when I4.0 technologies are adopted.

The variety of I4.0 technologies adopted enables a firm to use such technologies in various value chain activities. However, the penetration of I4.0 into the firm’s value chain activities (depth I4.0) does not per se directly imply the production of new knowledge, for which a firm needs internal collaboration among different business functions, in particular with the production area, or collaboration with external partners that favor I4.0 implementation, such as KIBS.

To achieve innovation goals by creating new knowledge, especially in the manufacturing industries, firms should encourage internal and external collaboration when I4.0 technologies are adopted. Moreover, policy makers should not only consider fiscal incentives for the adoption of such technologies, but also encourage the building of networks between adopting firms and external actors.

The study is one of the first attempt that provides empirical evidence of how I4.0 enables the creation of knowledge to innovate processes and products, highlighting the relevance of collaboration both within the company and with external partners.

The aim of this study was to identify interventions for and mechanisms of the digital transformation of purchasing and supply management (PSM) processes. The digital transformation of tactical and operational PSM processes has often progressed slowly despite the solid knowledge of advanced technologies.

This study used a qualitative exploratory approach based on 14 interviews with PSM executives from firms that are continuously working toward using advanced technologies in their PSM processes but have not yet gained full strategic benefits from digital transformation.

This study formulates five propositions regarding interventions and mechanisms that can positively influence the digital transformation of PSM processes. The main intervention in this regard is the renewal of data infrastructure, including platforms. PSM-related data should meet needs from both tactical and operational viewpoints. When applications serve as a source of data, they support digital transformation. Mechanisms such as supplier measurement and process improvement are outcomes of the digital transformation of PSM processes.

This study highlights the importance of common data sets for tactical and operational purchasing. These purchasing data should be owned and served by a cross-functional team. To create this interoperability, a firm needs global governance of open standards.

This study makes a theoretical contribution to the discussion of what kind of interventions positively influence on the digital transformation of PSM processes. Specifically, this study explains the integration needs of data and applications.

The purpose of this paper is to identify the potential and the challenges for different firms in adopting an AI-first strategy. The study attempts to discern if any company can prioritize AI at the forefront of their strategic plans.

Drawing from illustrative examples from well-known AI-leaders like Netflix and Spotify, as well as from upcoming AI startups and industry incumbents, the paper explores the strategic role of AI in core business processes and customer value creation. It also discusses the advent and implications of generative AI tools since late 2022 to firms’ business strategies.

The authors identify three types of AI-first strategies, depending on firms’ starting points: digital tycoon, niche carver and asset augmenter. The authors discuss how each strategy can aim to achieve data, algorithmic and execution advantages, and what the strategic bottlenecks and risks are within each strategy.

To the best of the authors’ knowledge, this paper is the first to systematically describe how companies can form “AI-first” strategies from different starting points. This study includes actionable examples from known industry players to more emerging startups and industrial incumbents.

Operational risks can cause considerable, atypical disturbances and impact food supply chain (SC) resilience. Indicatively, the COVID-19 pandemic caused significant disruptions in the UK food services as nationwide stockouts led to unprecedented discrepancies between retail and home-delivery supply capacity and demand. To this effect, this study aims to examine the emergence of digital platforms as an innovative instrument for food SC resilience in severe market disruptions.

An interpretive multiple case-study approach was used to unravel how different generations of e-commerce food service providers, i.e. established and emergent, responded to the need for more resilient operations during the COVID-19 pandemic.

SC disruption management for high-impact low-frequency events requires analysing four research elements: platformisation, structural variety, process flexibility and system resource efficiency. Established e-commerce food operators use partner onboarding and local waste valorisation to enhance resilience. Instead, emergent e-commerce food providers leverage localised rapid upscaling and product personalisation.

Digital food platforms offer a highly customisable, multisided digital marketplace wherein platform members may aggregate product offerings and customers, thus sharing value throughout the network. Platform-induced disintermediation allows bidirectional flows of data and information among SC partners, ensuring compliance and safety in the food retail sector.

The study contributes to the SC configuration and resilience literature by investigating the interrelationship among platformisation, structural variety, process flexibility and system resource efficiency for safe and resilient food provision within exogenously disrupted environments.

This study aims to analyse how multinational corporations (MNCs) organise value chain activities to penetrate new market segments. It contributes by expanding traditional decisions regarding the vertical fine-slicing of value chain activities (whether performed internally or externally) and the consideration of resource-sharing decisions (integration or separation) for each value chain function.

The authors draw on primary data collected from two case study firms operating in the large emerging Chinese market: Volvo Construction Equipment AB and Epiroc AB. In-depth cases illustrate how foreign MNCs expand into new market segments and simultaneously target both the lower-priced mid-market and the premium segments in the Chinese mining and construction industry.

The results reveal that product diversification creates challenges for managers who must oversee new (vertical) value chains, often simultaneously. Beyond geography and modes of governance, managers must decide whether to integrate or separate value chain activities for the new product lines. The study identifies four main strategic choices for firms to address this complexity, focusing on the decision to internalise or externalise (i.e. within or across organisational boundaries) and integrate or separate value chain activities between different product lines.

This study builds upon the internalisation theory and recent international business contributions that focus on value chain configurations to explain MNCs’ product diversification as a growth strategy in a host emerging market. It also sheds light on the choice of conducting new activities in-house or externally and elucidates firms’ managerial decisions to operationally integrate or separate individual value chain activities. The study provides insights into the drivers explaining managerial decisions to configure value chain activities across product lines and contributes to the growing body of literature on MNC activities in emerging economies by highlighting that product diversification impacts entry mode diversity and resource sharing across units.

This paper aims to illustrate the scope and challenges of using computer-aided content analysis in international marketing with the aim to capture consumer sentiments about COVID-19 from multi-lingual tweets.

The study is based on some 35 million original COVID-19-related tweets. The study methodology illustrates the use of supervised machine learning and artificial neural network techniques to conduct extensive information extraction.

The authors identified more than two million tweets from six countries and categorized them into PESTEL (i.e. Political, Economic, Social, Technological, Environmental and Legal) dimensions. The extracted consumer sentiments and associated emotions show substantial differences across countries. Our analyses highlight opportunities and challenges inherent in using multi-lingual online sentiment analysis in international marketing. Based on these insights, several future research directions are proposed.

First, the authors contribute to methodology development in international marketing by providing a “use-case” for computer-aided text mining in a multi-lingual context. Second, the authors add to the knowledge on differences in COVID-19-related consumer sentiments in different countries. Third, the authors provide avenues for future research on the analysis of unstructured multi-media posts.