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Low labor costs and market access are no longer competitive differentiators; increasingly companies are looking to design and develop new products and services as a crucial source of competitive advantage. As the pressure to innovate increases, so does the tension between shorter-term exploitative development and longer-term exploratory innovation activities. We explore this tension using interview data from software SMEs and venture capitalist firms who invest in technology-driven companies. Findings indicate that, despite firm’s having established solid innovation plans, short-term exploitative demands crowd out their longer-term exploration innovation during the development phase. Agency and resource dependence theories are used to start to explore some of the reasons for this shift. Implications and suggestions for future research are discussed.

Companies in all industries are searching for new sources of competitive advantage since the competition in their marketplace is becoming increasingly intensive. The resource-based view of the firm explains the sources of sustainable competitive advantages. From a resource-based view perspective, relational based assets (i.e., the assets resulting from firm contacts in the marketplace) enable competitive advantage. The relational based assets examined in this work are brand image and corporate reputation, as components of brand equity, and customer value. This paper explores how they create value. Despite the relatively large amount of literature describing the benefits of firms in having strong brand equity and delivering customer value, no research validated the linkage of brand equity components, brand image, and corporate reputation, simultaneously in the customer value–customer loyalty chain. This work presents a model of testing these relationships in consumer goods, in a business-to-business context. The results demonstrate the differential roles of brand image and corporate reputation on perceived quality, customer value, and customer loyalty. Brand image influences the perception of quality of the products and the additional services, whereas corporate reputation actions beyond brand image, estimating the customer value and customer loyalty. The effects of corporate reputation are also validated on different samples. The results demonstrate the importance of managing brand equity facets, brand image, and corporate reputation since their differential impacts on perceived quality, customer value, and customer loyalty. The results also demonstrate that companies should not limit to invest only in brand image. Maintaining and enhancing corporate reputation can have a stronger impact on customer value and customer loyalty, and can create differential competitive advantage.

The study here responds to the view that the crucial problem in strategic management (research) is firm heterogeneity – why firms adopt different strategies and structures, why heterogeneity persists, and why competitors perform differently. The present study applies complexity theory tenets and a “neo-configurational perspective” of Misangyi et al. (2016) in proposing complex antecedent conditions affecting complex outcome conditions. Rather than examining variable directional relationships using null hypotheses statistical tests, the study examines case-based conditions using somewhat precise outcome tests (SPOT). The complex outcome conditions include firms with high financial performances in declining markets and firms with low financial performances in growing markets – the study focuses on seemingly paradoxical outcomes. The study here examines firm strategies and outcomes for separate samples of cross-sectional data of manufacturing firms with headquarters in one of two nations: Finland (n = 820) and Hungary (n = 300). The study includes examining the predictive validities of the models. The study contributes conceptual advances of complex firm orientation configurations and complex firm performance capabilities configurations as mediating conditions between firmographics, firm resources, and the two final complex outcome conditions (high performance in declining markets and low performance in growing markets). The study contributes by showing how fuzzy-logic computing with words (Zadeh, 1966) advances strategic management research toward achieving requisite variety to overcome the theory-analytic mismatch pervasive currently in the discipline (Fiss, 2007, 2011) – thus, this study is a useful step toward solving the crucial problem of how to explain firm heterogeneity.

Introduction: In recent years, fresh big data ideas and concepts have emerged to address the massive increase in data volumes in several commercial areas. Meanwhile, the phenomenal development of internet use and social media has not only added to the enormous volumes of data available but has also posed new hurdles to traditional data processing methods. For example, the insurance industry is known for being data-driven, as it generates massive volumes of accumulated material, both structured and unstructured, that typical data processing techniques can’t handle.

Purpose: In this study, the authors compare the benefits of big data technologies to the needs for insurance data processing and decision-making. There is also a case study evaluation concentrating on the primary use cases of big data in the insurance business.

Methodology: This chapter examines the essential big data technologies and tools from the insurance industry’s perspective. The study also included an analytical analysis that supported several gains made by insurance companies, such as more efficient processing of large, heterogeneous data sets or better decision-making support. In addition, the study examines in depth the top seven use cases of big data in insurance and justifying their use and adding value. Finally, it also reviewed contemporary big data technologies and tools, concentrating on their key concepts and recommended applications in the insurance business through examples.

Findings: The study has demonstrated the value of implementing big data technologies and tools, which enable the development of powerful new business models, allowing insurance to advance from ‘understand and protect’ to ‘predict and prevent’.

Mobile marketing, the two- or multi-way communication and promotion of an offer between a firm and its customers using a mobile medium, device, platform, or technology, has made rapid strides in the past several years. Mobile marketing has entered its second phase or Mobile Marketing 2.0. The surpassing of desktop by mobile devices in digital media consumption, diffusion of wearable devices among customers, and an overall integration and interconnectedness of devices characterize this phase. Against this backdrop, we present a synthesis of the most recent literature in mobile marketing. We discuss three key advances in mobile marketing research relating to mobile targeting, personalization, and mobile-led cross-channel effects. We outline emerging industry trends in mobile marketing, including mobile app monetization, augmented reality, data and privacy, wearable devices, driverless vehicles, the Internet of Things, and artificial intelligence. Within each extant and emerging area, we delineate the future research opportunities in mobile marketing. Finally, we discuss the impact of mobile marketing on customer, firm, and societal outcomes.

In this paper, we offer insights that combine a network perspective of the multinational company (MNC) with an analysis of different types of interdependencies. We develop and illustrate our arguments with a company case (LIMO) and argue that types of interdependencies have consequences for the orchestration of MNC activities. The experience from LIMO suggests that extreme organizational designs, where orchestration is either purely local or mostly global, fail to capture the nuances necessary to ensure efficiency and profitability. The main theoretical contribution in this paper is to show that the search for orchestration through an organizational design must involve the combination of several perspectives of activity combinations and their interdependencies. Simply optimizing through a tight network or looking at the firm as a loose federation is too simple to understand the complex trade-off facing modern MNCs.