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Purpose: Innovation is a multi-dimensional phenomenon influenced at the organisational level by internal and external factors that can determine how innovative an organisation can be, determining a firm’s business performance. This chapter measures and predicts how innovative a company can be, considering key internal factors using modern data analytics/science.

Need for Study: The increasing challenge of modern business operations is affected by how quickly, sustainably, effectively, and efficiently companies can innovate to mitigate the dynamic challenges of current business environments and evolving customer needs. The ability to predict, measure, and manage innovation becomes necessary to ensure that businesses are fit for purpose.

Methodology: A model was designed following the study hypotheses and statistically tested. A historical data sample from the OECD global industry dataset for eight years was used for the analysis. The ordinary least square method was used to test for model fit. Also, in machine learning engineering, predictive analysis using the multivariate linear regression analysis method was carried out.

Findings: The results support the hypotheses that an organisation’s capacity to be innovative can be measured and predicted, and it is influenced by a good number of internal factors or independent variables at various degrees.

Practical Implications: Managers must understand how to measure and predict innovation metrics to manage innovation better, ultimately leading to better business outcomes and performance. Also proposed are new measurement matrices for innovation management: innovation capacity (I_C), business innovation value (BIV), innovation creation factor (ICF), and a practical data-driven innovation management and prediction system.

This paper reviews recent research on the expected economic effects of developing artificial intelligence (AI) through a survey of the latest publications, in particular papers and reports issued by academics, consulting companies and think tanks.

Our paper represents a point of view on AI and its impact on the global economy. It represents a descriptive analysis of the AI phenomenon.

AI represents a driver of productivity and economic growth. It can increase efficiency and significantly improve the decision-making process by analyzing large amounts of data, yet at the same time it creates equally serious risks of job market polarization, rising inequality, structural unemployment and the emergence of new undesirable industrial structures.

This paper presents itself as a building block for further research by introducing the two main factors in the production function (Cobb-Douglas): labor and capital. Indeed, Zeira (1998) and Aghion, Jones and Jones (2017) suggested that AI can stimulate growth by replacing labor, which is a limited resource, with capital, an unlimited resource, both for the production of goods, services and ideas.

Our study contributes to the previous literature and presents a descriptive analysis of the impact of AI on technological development, economic growth and employment.

The purpose of this study is to conduct a systematic literature review of the adoption of immersive marketing technology (IMT) in terms of strategic planning of its adoption, resource requirements and its implications and challenges.

This study categorizes and contextualizes qualitative approaches to evaluate the literature, with Scopus databases serving as the primary source of 90 selected articles in the areas of information technology, business and marketing strands. Theme analysis was carried out using thematic techniques and grounded approach principles to facilitate thematic coding and generate theme analysis.

The analysis was supported by the three concepts of business flexibility, agility and adaptability, which were drawn as a strategy for IMT adoption. The findings presented three main themes: proactive flexibility, responsive agility and reactive adaptability that enable business owner–managers to craft a strategy for IMT adoption.

The novel contribution of this study is the inclusion of key implications related to IMT as a starting point of the next level of innovative marketing for all academics, practitioners and business owner–managers.

Managers engage in marketing efforts to boost sales and in setting marketing budgets based on current or historical sales. Past studies have overlooked the reciprocal relationship between marketing spending and sales. This study aims to examine the nature of the relationship between sales and marketing expenses in the B2B market.

Five hypotheses on the relationship between sales and marketing expenditures were framed. A total of 30 of India’s dyeing firms provided data on revenues, sales (in units) and marketing expenditures over time. The structural vector auto-regressive model and the vector error correction model were fitted to the data.

The results show that marketing expenses and sales are related bidirectionally in a sequential way. Furthermore, sales drive the long-term equilibrium relationship to a greater extent than marketing expenditures.

The findings of this study should assist managers in predicting sales and marketing budgets simultaneously and devising precise marketing strategies and tactics.

Using econometric models in data-driven research is not a frequent practice in marketing. This study adds value to the body of marketing literature by advancing the theory of the relationship between sales and marketing spending using real-world data and econometric models in the B2B sector.

Industry 4.0 and the digital supply chain (DSC) are changing how things are made and moved around the world. This change is all about how smart technologies like the Internet of Things (IoT), artificial intelligence (AI), and blockchain are making supply chains work better. These tools help companies react faster and more clearly to what's needed. By using these new technologies, businesses can get better at guessing what customers want, keeping the right amount of stock, and quickly adjusting to new market trends. With these advanced technologies, companies can see big improvements, like being able to match supply with demand more closely and change their plans fast when things in the market change. It is really important for businesses to get how these tech tools work together as the world of making and selling things keeps changing. This chapter examines the convergence of traditional supply chain systems with Industry 4.0, focusing on the transformative impact of technologies such as the IoT, AI, and blockchain.

Although earlier research suggests a positive relationship exists between engaging in entrepreneurial marketing activities and firm performance, there may be contingent issues that impact the association. This investigation unpacks the relationship between entrepreneurial marketing behaviour and firm performance under the moderating role of coopetition, in an immediate post-COVID-19 period.

A resource-based theoretical lens, alongside an outside-in perspective, underpins this study. Following 20 field interviews, survey responses via an online survey were obtained from 306 small, passive exporting wine producers with a domestic market focus in the United States. The data passed all major robustness checks.

The statistical findings indicated that entrepreneurial marketing activities positively and significantly influenced firm performance, while coopetition provided a non-significant moderation effect. Field interviews suggested that entrepreneurs’ attemps to scale up from passive to more active export activities in an immediate post-pandemic period helped explain the findings. Owner-managers rejoined trustworthy and complementary pre-pandemic coopetition partners in the immediate aftermath of coronavirus disease 2019 (COVID-19) for domestic market activities. In contrast, they had to minimise risks from dark-side/opportunistic behaviour when joining coopetition networks with partners while attempting to scale up export market activities.

Unique insights emerge to unpack the entrepreneurial marketing–performance relationship via the moderation effect of coopetition, namely, with the temporal setting of an immediate post-COVID-19 period. Firstly, new support arises regarding the likely performance-enhancing impact of owner-managers’ engagement in entrepreneurial marketing practices. Secondly, novel findings emerge in respect of the contrasting role of coopetition in both domestic and export market activities. Thirdly, new evidence arises in relation to a resource-based theoretical lens alongside an outside-in perspective, whereby, strategic flexibility in pivoting facets of a firm’s business model needs effective management following a crisis.

Economic costs and benefits are at the core while taking decision to adopt digitalization in the supply chain. The present chapter provides an in-depth exploration of the economic dimensions of digital supply chain management (DSCM) adoption in a firm. Drawing from a diverse source of literature, this chapter discusses the effect of economic outlook on DSCM adoption, the economic benefits of DSCM adoption and costs associated with it, and economic analysis and evaluation methodologies. The chapter also shares the case studies illustrating the real-world implications of economic considerations within DSCM initiatives. The chapter highlights how changing international socioeconomic and political dynamics can influence businesses across the globe. By analyzing the impacts of evolving market trends, changing consumer preferences, and geopolitical tensions, organizations can considerably forecast the possible impacts of these macroeconomic forces adeptly. The chapter also undertakes discussion on the economic cost and benefits associated with DSCM adoption. The economic analysis helps understand that the expected benefits outweigh economic costs, substantiating the economic viability of DSCM projects. The chapter concludes by discussing the examples of some real-world companies, highlighting how organizations have successfully applied economic analyses to their DSCM initiatives. This also highlights as to how showcasing how detailed economic assessments can justify substantial investments, deliver operational efficiencies, and reshape industries.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

This research extends self-congruity theory and assesses the predictive validity of the triad personality congruence among brand, brand-related sustainability initiatives (BSI) and self-concept (BSSC: brand-sustainability-self-congruence) on consumers’ brand evaluation.

Three studies assessed BSSC using the brand personality scale (BPS) and the direct congruence measure (DCM). Through moderated mediation analyses, BSSC effects were examined on consumers’ behavioral intention, behavior and subjective well-being (SWB). The mediating role of brand trust and the moderating role of brand/BSI types and consumer characteristics were also assessed.

BSSC increased consumers’ brand trust, behavioral intention, behavior and SWB. Data based on BPS revealed impactful attributes that increase/decrease BSSC levels across brand-BSI combinations and the moderating role of sustainability involvement and income to enhance BSSC effects. BSSC was particularly effective, according to DCM.

For BSI planning, strategic consideration of BSSC based on both BPS and DCM is recommended. Thus, managers may predict the psychological impact of BSI and align its attributes to increase consumers’ brand evaluation.

In the sustainable marketing context, this research discusses BSSC – triad personality congruence – based on BPS and DCM and its predictive effects on consumers’ short-term brand evaluation, their actual behavior and SWB, a long-term life evaluation. The results imply a possible variation in consumers’ information processing according to the congruence measurement approach. Thus, it is relevant to the research on self-congruity, sustainability, marketing, consumer psychology/behavior and well-being.

This study aims to investigate the effect of social influence and value-driven mobile marketing activities on consumers’ acceptance of mobile marketing offers.

The method used is survey questionnaire. A proposed model was tested by using structural model analysis and data gathered from 356 Mexico consumers and 346 US consumers.

The study shows the number of peers and providing information are the main predictor variables of consumer acceptance of mobile marketing offers in both countries. These results suggest that social value factors are important variables for explaining consumers’ responses to mobile marketing offers across two countries characterized by dissimilar macro-environmental conditions.

The study’s overall implication about standardization vs adaptation is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries. One limitation in this study is the use of a convenience sample of undergraduate college students. This study did not control for different types of mobile phones and the screen sizes of mobile phones.

The overall implication of standardization vs adaptation from the study results is that social value messages can be standardized across countries. However, the marketing tools and touch points required to communicate any message appeal must be adapted across countries.

Unlike previous studies where the emphasis is to explicate the effect of value-oriented mobile activity, this study examines the combined effect of social influence and value-driven mobile activities on acceptance of mobile marketing.