An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance

This study examines the effect of big data powered artificial intelligence on customer knowledge creation, user knowledge creation and external market knowledge creation to better understand its impact on B2B marketing rational decision making to influence firm performance. The theoretical model is grounded in Knowledge Management Theory (KMT) and the primary data was collected from B2B companies functioning in the South African mining industry. Findings point out that big data powered artificial intelligence and the path customer knowledge creation is significant. Secondly, big data powered artificial intelligence and the path user knowledge creation is significant. Thirdly, big data powered artificial intelligence and the path external market knowledge creation is significant. It was observed that customer knowledge creation, user knowledge creation and external market knowledge creation have significant effect on the B2B marketing-rational decision making. Finally, the path B2B marketing rational decision making has a significant effect on firm performance.     

Analytics in the era of big data: The digital transformations and value creation in industrial marketing

Big data analytics has been a topical area in the past decade. Despite it is emphased as a promising tool for the B2B sectors, there is a short of academic studies about this phenomenon in the industrial markets. Existing big data analytics focuses more on the consumers' marketing aspect, while in fact both the consumers' data and the machine-generated transaction data can be gathered and analysed at the interorganisational level. Subsequently, there is a need to increase the attention on the B2B aspects of big data analytics and the interactions of stakeholders. This paper, therefore, investigates the digital transformation enabled by big data analytics in the industrial markets and provides a conceptual framework. It solicits research articles that provide insights into various industrial contexts of this topic and applied both qualitative and quantitative approaches to identify the big data gathering and applications for value creation.     

Entrepreneurial marketing of international high-tech business-to-business new ventures: A decision-making process perspective

Knowledge of how entrepreneurial marketing is conducted in industrial markets is currently rather weak. This study explores the marketing decision-making process of entrepreneurs undertaking entrepreneurial marketing in international new ventures (INVs) operating in high-tech business-to-business markets. A qualitative study conducted with entrepreneurs from four case firms reveals that due to the iterative, incremental, and co-creative nature of the process, marketing decision making in high-tech business-to-business INVs that is more effectual than causal results in more entrepreneurial marketing. A novel finding is that entrepreneurs alternate causal and effectual marketing forms as a result of their ambidextrous entrepreneurialism, and variations in the internal uncertainty, technological uncertainty, and any market turbulence faced by the firm. We develop a dynamic model presenting the alternation between effectual and causal processes, and the feedback loop of entrepreneurial marketing. The research offers implications for the management of organizations operating under conditions of uncertainty on how their decision-making processes can optimize entrepreneurial marketing, how to create new markets, and how to reduce the perceived uncertainty in industrial markets.     

Use of rules in decision-making in government outsourcing

The paper reports research on the nature of use of rules in decision making process by government entities in outsourcing commercial activities. The study used multiple data sources such as in-depth personal interviews of multiple categories of respondents, documentary evidence, and observation. The findings indicated that Government organizations use un-written ground rules as the main means of managing outsourcing processes.     

Artificial intelligence as an enabler of B2B marketing: A dynamic capabilities micro-foundations approach

Over the past few decades research has predominantly focused on the technical aspects and theoretical challenges of Artificial Intelligence (AI). With the deluge of data and the increase in processing power, businesses are now facing the challenge of how to deploy AI that generates business value. In this direction, there is still nascent research on how AI can be leveraged in for B2B operations, and particularly marketing. To address this gap, this study draws on the dynamic capabilities view of the firm and specifically on the micro-foundations approach and builds on three selected case studies of large organizations in Norway that use AI for B2B marketing purposes. The study identifies a number of AI-specific micro-foundations of dynamic capabilities, essentially highlighting how organizations can use AI to manage B2B marketing operations in dynamic and uncertain environments. This study also identified several key cross-cutting elements emerging from the data, demonstrating how some key concepts are inter-related and how they affect overall business value.     

Marketing research by a small industrial firm: A case study

There is a growing need today for industrial marketers to conduct marketing research and use the results in making profitable business decisions. This paper describes a marketing research study conducted by a small industrial firm and discusses the nature and extent of its impact on the firm's operations. Several implications and practical guidelines are derived for industrial marketers in general, based on the firm's marketing research experience.     

Big data analytics for supply chain relationship in banking

This paper reports how a commercial bank in Asia uses big data analytic as a tool to explore the internal B2B data to improve supply chain finance and the efficiency of marketing tactics and campaigns. A case study was conducted by analyzing two types of supply chain relationships: (1) supply chain relationships in the credit reports; (2) e-wiring transactions among supply chain companies. The results show that big data analytics is very useful in terms of improving the commercial banks' marketing and risk management performances. The case study also set a good example for B2B firms seeking to understand how they could leverage big data analytics to differentiate customer solutions, sustain profitability and generate new business values. Theorical and practical implications are also discussed.     

Differential effects of firm generated content on consumer digital engagement and firm performance: An outside-in perspective

Social media contains a massive amount of information, which provides researchers and practitioners with an invaluable source of data to conduct research from end-users' perspectives, in order to influence firm strategic choices. Although an extensive amount of research has been developed in B2C and B2B marketing context, few social media studies take a dive into potential linkages between external and internal marketing contexts in an industry specific paradigm. This study aims to bridge B2C and B2B social media marketing, by adopting the outside-in perspective as theoretical lens. Using a large-scale dataset, collected from a micro-blogging site, and consumer-oriented information assembled from multiple sources, we empirically examine the inter-relationship between firm-generated messages, consumer digital engagement, and firm sales performance in the movie industry. Theoretically, this study builds upon the outside-in perspective and extends the current knowledge of the outside-in perspective to the social media context. It also bridges the B2C and B2B marketing literature by demonstrating that the insight garnered from B2C social media interactions should be integrated into the B2B firm interactions, communications, and decision makings. Managerially, this study provides movie practitioners with important implications.     

Growth hacking: Insights on data-driven decision-making from three firms

Theoretical backgroundThe work explores how Big Data analysis can reshape marketing decision-making in B2B sector. Deriving from Data-Driven Decision-Making (DDDM) approach, the Growth Hacking model is employed to investigate the role of cognitive computing and big data analytics in redefining business processes.PurposeThe main objectives of the study are: 1) to assess how a data-driven orientation to the use of big data analytics and cognitive computing can reframe marketing decisions in B2B segment; 2) to explore whether the adoption Growth Hacking can be helpful in exploiting the opportunities offered by big data analytics and cognitive computing in B2B marketing.MethodologyThe paper is based on Action Research (AR) methodology that permits researchers to participate actively in the observation of businesses and to examine how decisions are undertaken and managed over time.ResultsThe main findings allow identifying the most common strategies and tactics employed in three companies operating in different B2B sectors to exploit the opportunities offered by cognitive computing and big data analytics according to a data-driven marketing approach. Based on the application of the Growth Hacking model, the tools of analytics and the main objectives, outcomes and implications on marketing decision-making are revealed.OriginalityThe identification of the main objectives and outcomes produced across the three dimensions of the Growth Hacking model (data analysis, marketing and programming) can help academics and practitioners to understand the main levers to attain marketing goals, such as the enhancement of relationship with customers (CRM), continuous learning and development of new products and potential innovation.     

Industrial market segmentation by the structure of the purchasing process

This article presents a methodology for segmenting industrial markets on the basis of functional involvement in phases of the purchasing decision process. A decision matrix is developed as a structured measurement instrument to collect information about the composition of decision making units within target firms. The implications of this segmentation approach for industrial marketing strategy formulation are discussed.     

To app or not to app: A business-to-business seller's decision

Although business-to-business (B2B) selling firms increasingly realize the benefits of adoption and usage of B2B mobile applications (apps), few studies examine this topic. Building on the technology organization environment and the technology acceptance model adoption frameworks, this research provides an integrative framework to identify and investigate the key determinants of B2B mobile apps for sellers that have not implemented B2B mobile apps for their buyers to use in their decision making. The results from 360 marketing executives at B2B selling firms indicate that perceived usefulness, top management support, and competitive pressure positively influence the decision to adopt B2B mobile apps in the near future. In addition, relative advantage and perceived ease of use indirectly affect adoption of B2B mobile apps through perceived usefulness. The research findings provide several theoretical and managerial implications related to B2B mobile apps adoption.     

Towards a typology of collusive industrial networks: Dark and shadow networks

The prevailing understanding of collusive B2B networks is primarily based on the theories of industrial economists and organizational criminologists. ‘Successful’ collusive industrial networks (such as price-fixing cartels) have been seen to endure due to formal managerial structures of coordination and control. In this paper, we seek to transcend and challenge the understanding of these illegal forms of co-opetition by drawing on evidence from an in-depth examination of four price-fixing cartels that were facilitated chiefly by marketers. Our contribution introduces the notion of ‘shadow networks’ (networks where although attempts are made to ensure secrecy, multilateral modes of network structure dominate akin to ‘normal’ managerial endeavours such as joint ventures) and ‘dark networks’ (networks which appear more opaque and secretive through the adoption of bilateral modes of network structure and limited bureaucracy) to illustrate the types of collusive network forms that may exist. In addition, this allows us to build a deeper understanding of collusive network forms and related inter-firm interaction for an industrial marketing audience. We provide implications for marketing practice, theory, and policy. Specifically, we outline how organizations and the marketing function can perform self-administered antitrust audits in order to help avoid breaches of antitrust. Further, we consider the importance of the two forms of collusive inter-firm networks uncovered where marketers have attempted to render these secret from antitrust agencies, introducing a relatively new line of inquiry to the industrial marketing literature.     

The impact of the product to service shift in industrial markets and the evolution of the sales organization

Marketing is undergoing a paradigmatic shift that involves a change in focus from the exchange of goods, which are usually manufactured output, to providing a service, which is fundamental to economic exchange (Vargo & Lusch 2004).Evidenced by three decades of marketing transformation in B2B (business-to-business) sales organizations, this paper examines the evolution of sales organizations as a result of the shift from product- to service-focused commerce. This paper also identifies areas of future research and practice in marketing. Findings suggest that the traditional product-focused sales organization will evolve in two directions. First, enhanced use of technology will reduce some traditional sales functions and even face-to-face contact. Second, customers who are important to marketers will experience improvements in the level of customer contact—leading to growth in customer-focused sales organizations and an increase in global account management teams. Changes in sales organizations will also lead to changes in the selection, training, and recruitment of salespeople as well as their roles.Direction for future research and managerial implications are highlighted throughout the paper as are changes likely to occur in sales organizations.     

Engineering consultants' perceptions of corporate branding: A case study of an international engineering consultancy

The corporate branding literature on B2B markets has developed fairly rapidly over the past decade. However, empirical support on employees' perception of corporate branding is very limited, particularly with respect to employees who fall outside the marketing/branding function within their organizations. This paper explores engineering consultants' views - as an under-researched context - on the implications of corporate branding. Findings reveal engineers' views about the significance of personal brands, the implications of incorporation, the ways in which corporate branding is carried out in their organizations, and associations of technical proficiency with the corporate brand. From the findings, four hypotheses have been developed for future research.     

Cognitive computing,Big Data Analytics and data driven industrial marketing

The integration of cognitive computing and big data analytics leads to a new paradigm that enables the application of the most sophisticated advances in information and communication technology (ICT) in business, including industry, business to business, and related decision-making process. The same paradigm will lead to several breakthroughs in the subfield of industrial marketing: a field both promising and extremely challenging. This special issue makes a case that cognitive computing and big data are a source of a new competitive advantage that, if properly embraced, will further consolidate industrial marketing management position in the of core the decision-making process of businesses operating locally and globally. In this vein, the value added of this special issue is twofold. On the one hand, this special issue communicates high quality research on big data analytics and data science as it is applied in industrial marketing management; On the other hand, it proposes a multidisciplinary approach to the study of the design, implementation and provision of sophisticated applications and systems necessary for data-driven industrial marketing decisions.     

Service guarantees as a base for positioning in B2B

Research in marketing has shown that service guarantees can contribute to gaining a competitive advantage. However, studies of perceived benefits have mostly been investigated in a consumer marketing context while prior research in B2B has been limited. Given the peculiarities of B2B marketing we investigate the value of service guarantees for industrial customers. We report findings from two studies of attitudes to service guarantees and their effects on purchase intentions and customers' willingness to pay a price premium. Our findings based on conjoint analysis show that service guarantees can deliver added value to B2B customers with implications for positioning strategies. Buyers in B2B markets are encouraged to consider the potential positioning effects of service guarantees for their organization.     

Key trends in business-to-business services marketing strategies: Developing a practice-based research agenda

The marketing of B2B services has become an important field of academic enquiry. Industrial Marketing Management scholars have contributed to building a robust body of scholarship on the role of services as an indispensable aspect of company’s strategic performance process. However, with digitization, there is a clear need for theoretical concepts and frameworks that can guide companies in the development of contemporary and strategic roadmaps for their B2B service marketing strategies and performance practice. This position paper outlines an agenda and delineates issues in B2B service delivery that need to be addressed to close the gap between service marketing theory and practice and collaborate on the development of strategic service capabilities for the industrial marketing space. More specifically, we identify and discuss the impact of 5 important trends shaping B2B services: 1) gamification, 2) personalization, 3) Mixed Reality (MR), 4) data visualization, and 5) privacy. On the basis of these, we will offer a number of specific directions for future research by industrial marketing researchers.     

Technology Transfer to the Private Sector: A Field Study of Manufacturer Buying behavior

Public sector R&D is an important source of new product technologies and concepts. If the transfer of these technologies to private sector manufacturers is viewed from a marketing perspective, manufacturing organizations can be analyzed as industrial "buyers." David Large and Donald Barclay report on case-based research that explores this technology buying process. Findings are induced that suggest: user value, patent/proprietary position, prototype efficacy, and strategic fit are the most important attributes of the transfer proposal; and business empathy and credibility are the most important attributes of the transfer agent. The R&D director is identified as a key influencer in the transfer decision and represented by a model of the director's attitude toward technology transfer proposals. The authors develop implications for public sector managers/agents and suggest opportunities for further research.     

You have not been archiving emails for no reason! Using big data analytics to cluster B2B interest in products and services and link clusters to financial performance

The potential of big data analytics when it comes to gaining business insights, such as market trends and consumer preferences, has captured the interest of both scholars and business practitioners. However, the extant literature has so far provided limited empirical evidence to demonstrate how big data analytics can create business value. To address this research gap, this paper followed a novel big data analytical approach that involved analysing email archives about product/services demand clusters in a B2B setting. We analysed 621 k emails exchanged between 2009 and 2018. We identified a number of discussion clusters that were considered proxies for the interest buyers expressed in the products/services on offer. These clusters and associated discussion trends were linked to the company's revenues and financial performance, showing good predictive power. In doing this, we have demonstrated how widely available data, such as emails, which all companies have, can be used to underpin new methods for the early identification and monitoring of product demand trends, informing marketing strategies.     

A literature review and future agenda for B2B branding: Challenges of branding in a B2B context

The existing body of research knowledge on brand management has been predominantly derived from business-to-consumer markets, particularly fast moving consumer goods and has only recently started to expand in other contexts. Branding in business-to-business markets has received comparatively little attention in the academic literature due to a belief that industrial buyers are unaffected by the emotional values corresponding to brands. This paper provides a critical discussion of the fragmented literature on business-to-business branding which is organized in five themes: B2B branding benefits; the role of B2B brands in the decision making process; B2B brand architecture; B2B brands as communication enablers and relationship builders; and industrial brand equity. Drawing on the gaps and contradictions in the literature the paper concludes by proposing an agenda for future research.