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The aim of this research is twofold: (1) to investigate when the effect of R&D investment on New Product Development (NPD) performance peaks – the sweet spot and (2) to analyze the influence of firms’ export activities on where that spot is. Drawing on the knowledge-based view (KBV), we argue that export intensity and export experience lead to differential effects on how R&D investments are converted into new products.

We test our conceptual framework using time lagged data and optimal-level analysis. The dataset consists of an unbalanced panel of 608,891 observations and 333,516 firms.

The results support the expected inverted U-shaped relationship between R&D investment and NPD performance. They also show moderating effects of export intensity and experience. Export intensity enhances innovation processes by enabling firms to stretch the points at which R&D investments eventually taper off. In contrast, export experience improves firms’ ability to convert R&D investments into NPD performance. Our results demonstrate that, all else equal, firms with relatively higher export experience can spend less on R&D and still achieve higher levels of NPD performance.

We contribute to the literature by investigating how export activities provide a valuable context for understanding the theoretical mechanisms that help explain the inverted U-shaped relationship between R&D investment and innovation. We show the effects of exporting activities on the precise points where the R&D investment–NPD performance relationship peaks, thereby identifying the optimal point within this nonlinear relationship.

This paper analyses J1 League and J2 League clubs during the period 2011–2020 to anticipate financial distress.

Data were collected for 29 professional football clubs competing in the J1 and J2 League for the financial years ending 2011–2020. Analysis was conducted using Altman’s Z-score methodology and additional statistical tests were conducted to measure differences between groups.

The results show significant cases of financial distress amongst clubs in both divisions and that clubs that have played predominantly in the J1 League are in significantly poorer financial health than clubs that have played predominantly in the J2 League. Overall, the financial situation in Japanese professional football needs to be monitored, a position that could be exacerbated by the economic crisis, caused by the coronavirus disease 2019 (COVID-19).

While the financial situation for a majority of the clubs in the J-League presents an austere picture, comparison with clubs in other leagues across Asia and Europe and understanding the different policies set by these leagues would enable us to understand whether the phenomenon of financial distress is common to other clubs and leagues across different countries and continents.

The paper recommends that J-League visit the existing club licensing criteria and implement equitable cost-control measures, such as implementing a cap on acceptable losses over a specified period or restricting overall expenditures as a percentage of the club’s revenue.

The paper extends the evidence base of measuring financial distress in professional team sports and is also the first paper of its kind to examine this in relation to Asian professional football.

In this chapter, we emphasise how Creative Artificial Intelligence (AI) can and will transform the practice of financial operations (FinOps). To do this, we first place AI in the context of FinOps and how operations need to change, explicitly using Creative AI to be faster, more accurate and more creative when assessing client needs. This is achieved by explaining how traditional approaches fall well short of the mark by highlighting their fundamental limitations and showcasing how AI helps to address those shortcomings. We also provide a detailed discussion of how AI is transforming finance operations when we focus on four discursive areas: (1) risk, (2) fraud detection, (3) predictive analytics and (4) trading algorithms. In all four areas, Creative AI supports many decisions that benefit the clients, improves customer service and guides financial institutions to allocate their resources more effectively. We elaborate throughout this text how AI, in particular by using methods such as natural language processing, generative adversarial networks (GANs) and other related techniques, can be understood as what we have termed ‘Explainable AI’ to address operational issues in the modern financial world creatively. As AI offers great disarming power, we also discuss the threats, limitations and specific pitfalls of AI adoption and use in financial contexts. This includes addressing clearly ethical and regulatory concerns, in addition to the technical ones.

Introduction: In today’s world of increasing competition, diminishing product differentiation, higher customer expectations, easy product replacements and lowering brand loyalty, organisations are evolving new marketing strategies for economic, societal and sustainability. Cause-related marketing (hereafter referred to as CRM), a strategic sustainable philanthropic practice, is the upcoming form of CSR. CRM plays an instrumental role in achieving self-brand connection and brand loyalty.

Purpose: To explore, integrate and interconnect concepts of CRM and self-brand connection to get more insights into the imperative role of CRM strategy in developing self-brand connections that can lead to brand loyalty in the most sustainable way. For this, CRM and self-brand connection, as proposed by societal marketing and branding literature, were explored. This chapter is a propositional inventory where the researcher has explored the antecedents of CRM strategy and its role in developing brand loyalty through self-brand connection.

Methodology: This chapter is centred upon the existing literature on sustainability, CRM and branding to understand better the relationships between dimensions and consequences of CRM and its interlinkage with brand loyalty.

Findings: The literature recommends that selected dimensions: Cause-brand fit, product type, altruistic motivation and brand credibility determine the effectiveness of CRM strategy. It also establishes the profound impact of attitude towards brand, brand perception and brand distinctiveness on self-brand connection. A theoretical framework based on the existing literature represents an amalgamated groundwork for developing effective, sustainable CRM strategies in conjunction with the self-brand connection. The proposed framework is distinct as no study conjoins the abovementioned concepts and aims to comprehend whether this integration is brand loyalty.

This chapter considers the challenges of applying engineering practices to knowledge. Knowledge cannot be managed like other forms of capital because it is tacit and intangible. Research has identified economic properties and behaviors that set it apart from physical and financial capital. The authors translate the economic typology of human, structural, and relational capital to Blackler’s four forms of characterizations: embrained, embodied, embedded, and encultured. Knowledge elicitation techniques are discussed, and aligned with Blakely’s four forms of characterizations.

This study aims to uncover the constraints of automation and the affordances of augmentation related to implementing artificial intelligence (AI)-powered systems across different task types: mechanical, thinking and feeling.

Qualitative study involving 45 interviews with various stakeholders in artistic gymnastics, for which AI-powered systems for the judging process are currently developed and tested. Stakeholders include judges, gymnasts, coaches and a technology vendor.

We identify perceived constraints of automation, such as too much mechanization, preciseness and inability of the system to evaluate artistry or to provide human interaction. Moreover, we find that the complexity and impreciseness of the rules prevent automation. In addition, we identify affordances of augmentation such as speedier, fault-less, more accurate and objective evaluation. Moreover, augmentation affords to provide an explanation, which in turn may decrease the number of decision disputes.

While the unique context of our study is revealing, the generalizability of our specific findings still needs to be established. However, the approach of considering task types is readily applicable in other contexts.

Our research provides useful insights for organizations that consider implementing AI for evaluation in terms of possible constraints, risks and implications of automation for the organizational practices and human agents while suggesting augmented AI-human work as a more beneficial approach in the long term.

Our granular approach provides a novel point of view on AI implementation, as our findings challenge the notion of full automation of mechanical and partial automation of thinking tasks. Therefore, we put forward augmentation as the most viable AI implementation approach. In addition, we developed a rich understanding of the perception of various stakeholders with a similar institutional background, which responds to recent calls in socio-technical research.

In the verge of assessing Muslims’ participation in stock market, present study delved into evaluating the influence of Islamic religiosity (IR) on Muslim investor’s financial engagement factors with respect to stock market (i.e. financial literacy [FL], Islamic financial literacy [IFL], behavioural factors [BF], Shariah compliance [SC], technology adoption [TA] and institutional support [IS]), stock market participation (SMP) and financial well-being (FWB). Further, this study aims to examine the mediating role of IFL, TA and SMP and moderating role of IS.

Using a mixed-methods approach, a structured survey questionnaire was administered and responses have been collected from 319 Muslim investors from South India using stratified random sampling. Further, data was analysed using SPSS 20.0 and AMOS 20.0 by implementing one-way ANOVA, measurement model and structural equation model to assess the differences, mediating and moderating roles.

In this study, it is discovered that IR significantly impacts Muslim investor’s financial engagement factors, SMP and FWB. Further, it is explored that IFL accelerates the impact of FL and SC on SMP. The results also demonstrated the intervening role of TA in enhancing SMP through BF and the mediating role of SMP among Muslim investors with strong IR to attain and enjoy FWB. Interestingly, our study also argued that when the IS is more, the effect of IR on SMP is high.

Geographical boundaries are restricted to India, where the study proposes future studies in Islamic countries to better understand the religious belief system of the investors, as SC may vary in different countries.

In accordance with the results, it is recommended that the regulatory bodies and institutions intervene, support and incorporate IFL and also provide user-friendly Tec platforms to monitor and filter stocks and financial products for SC.

The present study intends to tackle the misconception of Islamic values with respect to participating in the stock market and recommends to undertake policy and regulatory framework to ensure the inclusive development of this community.

To the best of the authors’ knowledge, no studies so far have pondered on the mediating role of SMP in enhancing the effectiveness of IR on their FWB. Further, this study collectively examines the influence of IR on various financial engagement factors affecting SMP leading to FWB.

Embodied intelligent robots are the iconic productivity of the Industry 4.0 era, and their potential to bring about a productivity surge mainly comes from the driving force of robots on innovation rather than efficiency. However, the dynamic impact of robots on the innovation capability of enterprises has not been empirically tested.

This study integrates panel vector autoregression and threshold effects to investigate this dynamic relationship by a multi-level analysis based on data of Chinese A-share manufacturing listed enterprises.

(1) The short-term momentum of industrial robot applications (IRA) on exploitative innovation (EII) is significant and the long-term momentum on exploratory innovation (ERI) is stronger. (2) EII affected by IRA is the main source of short-term total factor productivity (TFP) growth, while ERI is the driving factor for long-term TFP growth. (3) The impact of IRA on TFP exhibits a double-threshold effect based on ERI and follows a “stepped” incremental pattern. The promoting effect of IRA on TFP will significantly increase only when ERI surpasses certain thresholds.

Industrial robots accelerate the potential productivity growth in the long term, mainly coming from the augmented contribution of ERI, providing reference and inspiration for enterprises to fully utilize the endogenous growth potential of robots and implement innovation strategies. It also provides forward-looking guidance for organisations to undertake adaptive changes for the forthcoming AI economic revolution.