Historically, management theory has ignored the constraints imposed by the biophysical (natural) environment. Building upon resource-based theory, this article attempts to fill this void by proposing a natural-resource-based view of the firm—a theory of competitive advantage based upon the firm's relationship to the natural environment. It is composed of three interconnected strategies: pollution prevention, product stewardship, and sustainable development. Propositions are advanced for each of these strategies regarding key resource requirements and their contributions to sustained competitive advantage.

A natural resource-based view of the firm

What is Organizational Identity

Research addressing the micro-foundational theoretical entity of customer engagement (CE) has proliferated in recent years. In parallel, the macro-foundational theory of service-dominant (S-D) logic is thriving. While the fit of CE/S-D logic has been recognized, insight into this theoretical interface remains tenuous, as explored in this paper. We develop an integrative, S-D logic–informed framework of CE comprising three CE foundational processes, which are required (for customer resource integration), or conducive (for customer knowledge sharing/learning) CE antecedents. While customer resource integration, in some form, extends to coincide with CE, customer knowledge sharing/learning can also do so. We also identify three CE benefits (customer individual/interpersonal operant resource development, cocreation) as CE consequences, which can also coincide with CE. Deploying the framework, we revise Brodie et al.’s (Journal of Service Research, 14(3), 252–271, 2011) fundamental propositions of CE and apply these to customer relationship management. We conclude with theoretical and managerial implications, followed by future research avenues.

https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=6786&context=lkcsb_research

S-D logic–informed customer engagement: integrative framework, revised fundamental propositions, and application to CRM

https://research.vu.nl/ws/files/98445568/Stage_to_Engage_KLM_Tourism_Management_2015.pdf

A stage to engage: Social media use and corporate reputation

Examines the motivation for achievement as a psychological factor that shapes economic development. Refuting arguments based on race, climate, or population growth, the book instead argues for cultural customs and motivations - especially the motivation for achievement - as the major catalysts of economic growth. Considering the Protestant Reformation, the rise of capitalism, parents' influences on sons, and folklore and children's stories as shaping cultural motivations for achievement, the book hypothesizes that a high level of achievement motivation precedes economic growth. This is supported through qualitative analysis of the achievement motive, as well as of other psychological factors - including entrepreneurial behavior and characteristics, and available sources of achievement in past and present highly achieving societies. It is the achievement motive - and not merely the profit motive or the desire for material gain - that has advanced societies economically. Consequently, individuals are not merely products of their environment, as many social scientists have asserted, but also creators of the environment, as they manipulate it in various ways in the search for achievement. Finally, a plan is hypothesized to accelerate economic growth in developing countries, by encouraging and supplementing their achievement motives through mobilizing the greater achievement resources of developed countries. The conclusion is not just that motivations shape economic progress, but that current influences on future people's motivations and values will determine economic growth in the long run. Thus, it is most beneficial for a society to concentrate its resources on creating an environment conducive to entrepreneurship and a strong ideological base for achievement. (CJC)

The Achieving Society

Dynamic programming models play a significant role in maximizing customer lifetime value (CLV), in different market types including B2B, B2C, C2B, C2C and B2B2C. This paper highlights the main contributions of applying dynamic programming models in CLV as an effective direct marketing measure. It mainly focuses on Markov Decision Process, Approximate Dynamic Programming (i.e. Reinforcement Learning (RL)), Deep RL, Double Deep RL, finally Deep Quality Value (DQV) and Rainbow models. It presents the theoretical and practical implications of each of the market types. DQV and Rainbow models outperform the traditional dynamic programming models and generate reliable results without overestimating the action values or generating unrealistic actions. Meanwhile, neither DQV nor Rainbow has been applied in the area of direct marketing to maximize CLV in any of the market types. Hence, it is a recommended research direction.

/pdf/maximizing-customer-lifetime-value-using-dynamic-programming-2g4h7r41d3.pdf

Maximizing Customer Lifetime value using Dynamic Programming: Theoretical and Practical Implications

This paper reviews the developments taking place in the Higher Education (HE) industry. The focus of the research is to identify the main variables used to segment universities in Egypt. The research is qualitative in nature as the dimensions for segmentation were derived based on a series of in-depth interviews followed by two focus groups. Perceived quality and level of internationalization were found to be the two most important dimensions for classifying HE institutions in Egypt. These two dimensions formed the basis of a two-by-two matrix, which was used to segment HE universities into four main segments. The four HE segments that were identified are: legacy, prestigious, imitators, and the uncertain. Each quadrant was identified based on the level of perceived quality and the degree of internationalization. The matrix is useful for universitiesâ€™ administrators to identify their current position and assess their future positioning strategies.

Identifying the Basis for Segmenting Higher Education: Evidence from Egypt

Customer lifetime value (CLV) is the most reliable indicator in direct marketing for measuring the profitability of the customers. This motivated the researchers to compete in building models to maximize CLV and consequently, enhancing the firm, and the customer relationship. This review paper analyzes the contributions of applying dynamic programming models in the area of direct marketing, to maximize CLV. It starts by reviewing the basic models that focused on calculating CLV, measuring it, simulating, optimizing it or -rarely- maximizing its value. Then highlighting the dynamic programming models including, Markov Decision Process (MDP), Approximate Dynamic Programming (ADP), also called Reinforcement Learning (RL), Deep RL and Double Deep RL. Although, MDP contributed significantly in the area of maximizing CLV, it has many limitations that encouraged researchers to utilize ADP (i.e. RL) and recently deep reinforcement learning (i.e. deep Q network). These algorithms overcame the limitations of MDP and were able to solve complex problems without suffering from the curse of dimensionality problem, however they still have some limitations including, overestimating the action values. This was the main motivation behind proposing double deep Q networks (DDQN). Meanwhile, neither DDQN nor the algorithms that outperformed it and overcame its limitations were applied in the area of direct marketing and this leaves a space for future research directions.

Dynamic programming models for maximizing customer lifetime value: An overview

In this study we aim to explore internal marketing applications in Egypt There is no evidence about the extent of internal marketing understanding and its applications Thus, we explore it by presenting some case studies and conducting some in-depth interviews This paper is based on a combination of secondary and primary research Some cases of companies that apply internal marketing practices are presented and discussed In addition, a series of in-depth interviews with top-level managers were conducted to examine their views about internal marketing practices in their organizations The findings provided some evidence that there are some companies that apply internal marketing in Egypt This was identified from the secondary research case studies However, when the qualitative interviews were conducted, it was found that there was lack of a clear understanding by many companies about what is internal marketing and methods for applying internal marketing This study provides some insights as to internal marketing practices at Egyptian companies The paper is useful for managers who want to know more about internal marketing applications and practices This study sets the pace for more future work on this untapped research area

/pdf/exploring-internal-marketing-applications-case-of-egypt-46w2hu3a8y.pdf

Exploring Internal Marketing Applications: Case of Egypt

\nPurpose\nThe purpose of this paper is to close the gap between the theoretical nature of existing contributions in customer engagement value (CEV) and its need to practically empower business decisions. This is done by proposing a framework that consists of three techniques, each of which combines the components of CEV to make it more comprehensive and applicable. The paper also reviews and analyzes the work that has been done so far in the area of CEV whether in business to business (B2B), business to consumer (B2C) or consumer to consumer (C2C) markets.\n\n\nDesign/methodology/approach\nCEV is a comprehensive term that measures the total value of the customer through capturing his transactional and non-transactional behaviors. Hence, it is an essential term for measuring the value of the customer in direct marketing. This motivates researchers to compete in developing models to maximize CEV. Meanwhile, most of the existing models are conceptual and the majority of them lack applicability due to many reasons. First, these models relied on a linear version of the CEV model, hence double-counting the value of the customer; also they weighted the components of CEV equally, which is unrealistic. Finally, the effect of the environmental components in determining the engagement level of each customer was almost ignored. In this paper, two main contributions are presented. First, a summary and analysis of the contributions of the literature in the CEV field for different market types whether in B2C, B2B or C2C. Furthermore, three modifications are added to the existing models. The first model introduces a non-linear relationship of the components of CEV. The second model is a weighted linear model of these components. Finally, the third model adds the environmental factors to the CEV components. All the proposed models are theoretical in nature, however, these models are expected to show superiority when being applied to real data sets due to their ability to capture the complexity in the relationship between the firm and its customers in real-life situations. The proposed models are expected to attract the practitioners and other researchers and they both are encouraged to apply the proposed models on real-life data sets, test their performance, compare them against each other, to be able to apply each of them on the best suitable data set and business scenario.\n\n\nFindings\nBased on the review and analysis that has been done on about 87 papers, it is found that the majority of the contributions that have been done in the area of CEV are theoretical in nature, in spite of the effectiveness of CEV in empowering business decision. It is also found that few researchers proposed a set of theoretical comprehensive frameworks that combined CEV’s components together. Meanwhile, those frameworks are not practically applicable.\n\n\nResearch limitations/implications\nAlthough the contribution of the proposed models expected to attract both researchers and practitioners, these are not applied to real-life case studies to prove their effectiveness.\n\n\nPractical implications\nThe research in this paper has many industrial and managerial implications. First, it helps managers and decision takers to treat the customers as assets and cost-free resources who can work with the firm to achieve what’s both aims to (i.e. increase customer satisfaction and firm’s profitability). Second, it helps the firm to determine the total value of each customer and treat its customers accordingly. Third, it empowers the managers to do target marketing, based on grouping the customers upon their total engagement. This would save time and cost and for sure increase the profitability and customer satisfaction. Forth, the proposed models take into consideration not only the transactional behavior of the customers but also the non-transactional factors that play a significant role in formulating the relationship between the firm and its customers.\n\n\nOriginality/value\nThis is hereby to certify that the paper is original, neither the paper nor a part of it is under consideration for publication anywhere else. Also, this study has no conflicts of interest to disclose.\n

Hamed M. Shamma

Papers

Maximizing Customer Lifetime value using Dynamic Programming: Theoretical and Practical Implications

Identifying the Basis for Segmenting Higher Education: Evidence from Egypt

Dynamic programming models for maximizing customer lifetime value: An overview

Exploring Internal Marketing Applications: Case of Egypt

Customer engagement value: process, limitations and future research