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In the era of Big Data, larger volumes of data arrive in various forms at an increasing pace but of questionable quality and value. The abundant information (that emanates from these 5Vs – volume, variety, velocity, veracity, and value) taxes the bounded capacity of managers. This chapter introduces a taxonomy of approaches available for strategic decision making in an information-rich environment, several of which showcase that automation can help to augment (not supplant) managerial decision making. This taxonomy is then applied to an innovation context. Mapping a stylized version of the phases of the innovation process (i.e., front-end innovation, new product development, commercialization) onto the four decision-making approaches yields an organizing framework for understanding strategic decision making in the realm of innovation. The chapter concludes by identifying promising areas for future research.

This conceptual chapter: (1) explicates the foundational terminology regarding strategic decision making in a marketing context; (2) provides a primer on the era of Big Data and making strategic decisions in an information-rich environment; (3) introduces a taxonomy, which features approaches to decision making in an information-rich environment; and (4) applies the taxonomy in an innovation context to yield an organizing framework.

This chapter focuses on the nascent field that is emerging at the intersection of innovation, marketing strategy, and information-rich environments, and breaks new ground by exploring automation available to aid managerial decision making in this realm.

The main practical implication is to elucidate that managers can apply different approaches to decision making in today’s information-rich environment. Tables 2–4 provide to managers 12 examples of the types of decision making in an innovation context.

This chapter introduces a new taxonomy to classify four approaches for making strategic decisions in an information-rich environment, and extends that framework to the innovation realm. This framework aims to prompt researchers to explore important topics that exist at the intersection of innovation, marketing strategy, and managerial decision making in an information-rich environment.

In today’s dynamic business environment, it’s crucial for companies to employ robust strategies and decision-making tools to remain competitive. This chapter explains the key comprehensive policies that can be applied by any company to maximise the effectiveness of the APPNIE framework. These policies include the following key elements for effective use of the APPNIE model: appointing an APPNIE manager responsible for maintaining and updating the model, collaborating with top executives, and formulating action plans; raising awareness of the APPNIE manager’s role across the organisation to encourage sharing valuable information (establishing clear procedures and channels for data collection); encouraging the communication of valuable data by offering recognition or rewards, ensuring a steady flow of filtered information; monitoring the eight quadrants using qualitative and quantitative data for up-to-date assessments of key APPNIE’s factors; organising regular meetings between APPNIE managers and directors from different functions to share perspectives, discuss action plans, and address challenges and opportunities. The chapter shows that by adopting these practices, companies can navigate ‘complexity’, make informed decisions, and enhance their overall success and competitiveness in the market.

While Big Data offer marketing managers information that is high in volume, variety, velocity, and veracity (the 4Vs), these features wouldn’t necessarily improve their decision-making. Managers would still be vulnerable to confirmation bias, control illusions, communication problems, and confidence issues (the 4Cs). The authors argue that traditional remedies for such biases don’t go far enough and propose a lean start-up approach to data-based learning in marketing management. Specifically, they focus on the marketing analytics component of Big Data and how adaptations of the lean start-up methodology can be used in some combination with such analytics to help marketing managers improve their decision-making and innovation process. Beyond the often discussed technical obstacles and operational costs associated with handling Big Data, this chapter contributes by analyzing the various learning and decision-making problems that can emerge once the 4Vs of Big Data have materialized.

The purpose of the chapter is to determine the perspective directions of improving the process of decision-making in business systems by the example of modern Russia.

The scientific and methodological platform of this research is the Russian model of decision-making in modern business systems. For determining the perspective directions of improvement of the process of decision-making in business systems according to this model, the methods of systemic and problem analysis, modeling, and formalization are used.

It is shown by the example of modern Russia that perspectives of improving the process of decision-making in business systems are connected not to usage of alternative regional models of this process but to modernization of own models by usage of new organizational tools and innovational technologies. The perspective directions of improving the process of decision-making in business systems of modern Russia include development of systemic feedback and marketing with the help of outsource, increase of flexibility of organizational structure with the help of mediation, and usage of means of authomatization of managerial decisions with the help of intellectual technologies.

The compiled improved Russian model of decision-making in a modern business system showed the advantages of practical implementation of the offered perspective directions, connected to the most complete solution of the problem and implementation of possibilities of the business system, accelerated practical implementation of managerial decisions, and reduced the load on business managers. The presented example of improving the Russian model of managerial decisions in modern business systems reflects the possibilities and perspectives of improving other regional models.

Over the past 25 years as a marketing academic, I have been fortunate to have collaborated with various researchers and firms and have contributed to the advancement of the marketing field. This is a review article that tracks my progress through these years that has led me to explore different areas of marketing, thereby shaping me as a researcher and an academic. As I see now, all of my research work can be viewed from a decision-making point of view – decisions that marketers can make either at the market, brand/firm/store, or the customer level. These decisions have in turn been transformed into strategies or tactics leading up to successful implementations and improved bottom-line results. The development of strategies/tactics and successful implementations can be seen in nearly 10 areas of research that I have involved myself in. This article also highlights how my research studies have contributed and advanced the creation of knowledge in each of these research areas.

This chapter points out that the use of a wide range of theoretical paradigms in marketing research requires researchers to use a broad range of methodologies. As an aid in doing so, the chapter argues for the use of case study research (CSR), defines CSR, and describes several CSR theories and methods that are useful for describing, explaining, and forecasting processes occurring in business-to-business (B2B) contexts. The discussion includes summaries of six B2B case studies spanning more than 60 years of research. This chapter advocates embracing the view that learning and reporting objective realities of B2B processes is possible using CSR methods. CSR methods in the chapter include using multiple interviews (2 + ) separately of multiple persons participating in B2B processes, direct research and participant observation, decision systems analysis, degrees-of-freedom analysis, ethnographic-decision-tree-modeling, content analysis, and fuzzy-set qualitative comparative analysis (fs/QCA.com). The discussion advocates rejecting the dominant logic of attempting to describe and explain B2B processes by arms-length fixed-point surveys that usually involve responses from one executive per firm with no data-matching of firms in specific B2B relationships – such surveys lack details and accuracy necessary for understanding, describing, and forecasting B2B processes.

Information and communications technology (ICT) offers enormous opportunities for individuals, businesses and society. The application of ICT is equally important to economic and non-economic activities. Researchers have increasingly focused on the adoption and use of ICT by small and medium enterprises (SMEs) as the economic development of a country is largely dependent on them. Following the success of ICT utilisation in SMEs in developed countries, many developing countries are looking to utilise the potential of the technology to develop SMEs. Past studies have shown that the contribution of ICT to the performance of SMEs is not clear and certain. Thus, it is crucial to determine the effectiveness of ICT in generating firm performance since this has implications for SMEs’ expenditure on the technology. This research examines the diffusion of ICT among SMEs with respect to the typical stages from innovation adoption to post-adoption, by analysing the actual usage of ICT and value creation. The mediating effects of integration and utilisation on SME performance are also studied. Grounded in the innovation diffusion literature, institutional theory and resource-based theory, this study has developed a comprehensive integrated research model focused on the research objectives. Following a positivist research paradigm, this study employs a mixed-method research approach. A preliminary conceptual framework is developed through an extensive literature review and is refined by results from an in-depth field study. During the field study, a total of 11 SME owners or decision-makers were interviewed. The recorded interviews were transcribed and analysed using NVivo 10 to refine the model to develop the research hypotheses. The final research model is composed of 30 first-order and five higher-order constructs which involve both reflective and formative measures. Partial least squares-based structural equation modelling (PLS-SEM) is employed to test the theoretical model with a cross-sectional data set of 282 SMEs in Bangladesh. Survey data were collected using a structured questionnaire issued to SMEs selected by applying a stratified random sampling technique. The structural equation modelling utilises a two-step procedure of data analysis. Prior to estimating the structural model, the measurement model is examined for construct validity of the study variables (i.e. convergent and discriminant validity).

The estimates show cognitive evaluation as an important antecedent for expectation which is shaped primarily by the entrepreneurs’ beliefs (perception) and also influenced by the owners’ innovativeness and culture. Culture further influences expectation. The study finds that facilitating condition, environmental pressure and country readiness are important antecedents of expectation and ICT use. The results also reveal that integration and the degree of ICT utilisation significantly affect SMEs’ performance. Surprisingly, the findings do not reveal any significant impact of ICT usage on performance which apparently suggests the possibility of the ICT productivity paradox. However, the analysis finally proves the non-existence of the paradox by demonstrating the mediating role of ICT integration and degree of utilisation explain the influence of information technology (IT) usage on firm performance which is consistent with the resource-based theory. The results suggest that the use of ICT can enhance SMEs’ performance if the technology is integrated and properly utilised. SME owners or managers, interested stakeholders and policy makers may follow the study’s outcomes and focus on ICT integration and degree of utilisation with a view to attaining superior organisational performance.

This study urges concerned business enterprises and government to look at the environmental and cultural factors with a view to achieving ICT usage success in terms of enhanced firm performance. In particular, improving organisational practices and procedures by eliminating the traditional power distance inside organisations and implementing necessary rules and regulations are important actions for managing environmental and cultural uncertainties. The application of a Bengali user interface may help to ensure the productivity of ICT use by SMEs in Bangladesh. Establishing a favourable national technology infrastructure and legal environment may contribute positively to improving the overall situation. This study also suggests some changes and modifications in the country’s existing policies and strategies. The government and policy makers should undertake mass promotional programs to disseminate information about the various uses of computers and their contribution in developing better organisational performance. Organising specialised training programs for SME capacity building may succeed in attaining the motivation for SMEs to use ICT. Ensuring easy access to the technology by providing loans, grants and subsidies is important. Various stakeholders, partners and related organisations should come forward to support government policies and priorities in order to ensure the productive use of ICT among SMEs which finally will help to foster Bangladesh’s economic development.

The purpose of the research is to study the successful global experience of managerial decisions in modern business systems.

The authors use the method of systematization, logical analysis (analysis of causal connections), and formalization. The information and empirical basis of the chapter includes the materials of research of an international consulting company Hay Group, devoted to evaluation of effectiveness of decision-making in companies of Europe, Russia, and other markets and compilation of the global ranking of the best companies for leaders in 2018, as well as statistical data of Samuel Centre for Social Connectedness and World Economic Forum for 2018.

The studied and analyzed successful global experience of decision-making in modern business systems showed that the key factors of successful managerial decisions are complexity of organizational structure, characteristics of organizational culture, level of marketing activity, and personal qualities of leaders (business managers). However, the influence of these factors is contradictory – they stimulate observation of certain criteria of optimality and hinder observation of other criteria.

It is determined that observation of all criteria of optimality of managerial decisions is not guaranteed by any regional model of business systems. Emphasis on certain criteria (e.g., speed of decision-making in countries of Asia) leads to decrease of general results (global competitiveness and ecological effectiveness of business systems).