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Welcome to the Library

Hello. Why don’t you pull up one of those nice comfy chairs. Go on, settle yourself down in front of the crackling fire, with a good cup of tea (or coffee, or something stronger, the choice is yours).

This is my virtual library where I list the books and articles that have sparked my interest and thoughts. I’m not intending to give a detailed review of these books. Rather, just to highlight points of interest.

If you’re looking for the list of references, then you should try here.

I hope you find the items in the library as interesting and thought inspiring as I have! If you’ve got any comments or suggestions of other books and articles, please let me know!

Customer Resistance to Tourism Innovations: Entrepreneurs’ Understanding and Management Strategies

Sanchez, I., Williams, A., García-Andreu, H. (2019)

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Research Paper
Abstract: Customer resistance is the greatest risk to innovation for the entrepreneur. The aim of this exploratory study is to provide insights into this underdeveloped area in the tourism innovation literature. A qualitative approach is adopted to understand the resistance experienced by 57 entrepreneurs when introducing their innovations into the market, the causes and the actions taken to minimise resistance. Findings indicate that most entrepreneurs often encounter resistance from sceptical customers, satisfied with their status quo and with no or low appetites for innovation. The analysis reveals two main sources of resistance: the association of the innovations with particular risks, and the customers' lack of understanding of the innovation value. Communication strategies are crucial to decrease the associated risks and for trust building. The paper provides a critical perspective on the challenges faced by innovators, challenges which are often overlooked given the near-iconic status of innovation in studies of economic development.


Looks at 57 entrepreneurs and resistance to innovation in the tourism industry. Includes a conceptual model on what to do in the face of postponement, rejection and opposition
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Customer’s operant resources effects on co-creation activities

Alves H., Ferreira J.J., Fernandes C.I. (2016)

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Research Paper
Abstract: This study analyses the influence of client operant resources, in the form of self-efficacy, bridging social capital and customer expertise, on co-creation activities with companies and the customer resulting perceived benefits. A quantitative study, based on a sample of 362 consumers was carried out to test a model that sets out the relationships among the variables in analysis. The results demonstrate not only how operant resources do effectively contribute towards explaining a certain percentage of the variation in customer co-creation activities, but also how this resources influence gets boosted by the efforts companies make to educate their customers. The results also show that co-creation with the firm enhances customer perceived benefits.


Study showing customer operant resources and impact on co-creation of value/perceived benefits
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Defining Service Innovation: A review and Synthesis

Witell, L., Snyder, H., Gustafsson, A., Fombelle P. W.  (2016)

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Research Paper
Abstract: Research on service innovation appears in several research disciplines, with important contributions in marketing, management, and operations research. Although the concept is widely used, few research papers have explicitly defined service innovation. This dearth of research is the motivation for the present study. Through a systematic review of 1301 articles on service innovation appearing in academic journals between 1979 and 2014, this article examines research defining service innovation. The study identifies the key characteristics within 84 definitions of service innovation in different perspectives (assimilation, demarcation and synthesis) and shows how the meaning of the concept is changing. The review suggests that the large variety in definitions limits and hinders knowledge development of service innovation.


This paper reviews service innovation from 1301 papers spanning 1979-2014. It points out the limited amount of research that has been conducted; is helpful in giving the context and definitions from the three perspectives of assimilation, demarcation and synthesis; and identifies that such a wide range of definitions hinders knowledge development.
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Designing Interactive Strategy

Normann, R., Ramírez, R. (1993)

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Research Paper
“IKEA is more than a link on a value chain. It is the center of a constellation of services, goods, and design.” “In essence, the [Danish] pharmacies wanted to broaden their traditional approach, delivery of conventional pharmaceutical “hardware” (in other words, selling drugs), into a concept they called Pharmaceutical Care, which would emphasize the “software” […]
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DiffuNET: The impact of network structure on diffusion of innovation

Liu, B., Madhavan, R., Sudharshan, D. (2005)

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Research Paper
Abstract: Purpose – To provide an explicit model to address the relationships between the structural characteristics of a network and the diffusion of innovations through it. Further, based on the above relationships, this research tries to provide a way to infer diffusion curve parameters (innovation coefficient and imitation coefficient) from network structure (e.g. centralization). Design/methodology/approach – Based on the network and innovation literatures, we develop a model explicitly relating the structural properties of the network to its innovation and imitation potential, and in turn to the observed diffusion parameters (innovation and imitation coefficients). We first employ current theoretical and empirical results to develop postulates linking six key network properties to innovation and imitation outcomes, and then seek to model their effects in an integrative manner. We argue that the innovation and imitation potentials of a network may be increased by strategically re-designing the underlying network structure. We validated the model by searching the published empirical literature for available published data on network properties and innovation and imitation coefficients. Findings – We validated the model by searching the published empirical literature for available published data on network properties and innovation and imitation coefficients. The results reported from various relevant research papers support our model. Practical implications – This research shows that the innovation and imitation potentials of a network may be increased by strategically re-designing the underlying network structure; hence, provide guidelines for new product managers to enhance the performance of innovative products by re-design the underlying network structure.


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Diffusion Model for the Adoption of Smartphone Brands under Competitive Pricing

Ashokan, R., Zenarosa, G. L., He, X. (2018)

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Research Paper
Abstract: We extend the Bass diffusion model to capture the dynamic adoption and competitive pricing of two smartphone brands: Apple and Samsung. We use publicly available historical data to regress the model parameters. We find our model to reasonably fit the data, and we provide some insights on the competition between the smartphones brands with respect to our model and the available data.


I use part of the graph in this paper in my discussion of Bass’ model of diffusion.
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Diffusion of Innovations

Rogers, E. M. (2003)

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Book
Work in Progress
[In Progress] Rogers looks at how new ideas spread via communication channels over time, coming up with an adoption/diffusion curve. This curve shows how the diffusion process starts with a few individuals who first adopt an innovation (innovators) and spread the word among their circle (early adopters). These early adopters spread the word to the early majority, then in turn to the late majority, finally ending up with the laggards.Understanding adoption/diffusion is key in product innovation, and also a key base in service innovation (where there are also additional factors to take account of)
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Diffusion of new products: empirical generalizations and managerial uses

Mahajan, V., Muller, E., Bass, F.M. (1995)

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Research Paper
Abstract: The diffusion model developed by Bass (1969) constitutes an empirical generalization. It represents a pattern or regularity that has been shown to repeat over many new products and services in many countries and over a variety circumstances. Numerous and various applications of the model have lead to further generalizations. Modifications and extensions of the model have lead to further generalizations. In addition to the empirical generalizations that stem from the model, we discuss here some of the managerial applications of the model.


Summarises research into coefficients p and q in Bass’ model and gives average, min and max observed values. Takes Rogers’ standard decision based adopter categories and reapplied with this model and practice. Percentages are remarkably close, but there are differences. Especially in innovators: 0.2-2.8% compared to Rogers fixed 2.5%. And in early adopters: 9.5-20% compared […]
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Diffusion of Technology Generations: A Model of Adoption and Repeat Sales (Working Paper)

Bass, F., Bass, P. I. (2011)

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Research Paper
Abstract: This paper explores multiple-generation demand dynamics of “fast-tech” products, which we define as durable technological products and technology-based services where repeat purchases are motivated by user-perceived functionality increases that trigger generational transitions. Examples of fast-tech products include: personal computers (PCs), DRAMs, printers and wireless telephone services. In management of fast-tech products, special attention must be paid to the different needs of adopters and repeaters, which may require different product, advertising and distribution-channel strategies. We develop a model of multiple-generation product diffusion in which sales are constructed as the sum of adoption sales and repeat sales thus, for the first time, separately identifying first-time purchases and repeat purchases. The model also identifies (1) the potential market for each generation, (2) total systems in use (subscribers if a service market) by time period and (3) systems-in-use (installed-base) mix by product/service generation for each time period. The model reduces to the basic Bass model (1969) in the case of a single generation. We use two sets of empirical data (eight DRAM generations and nine PC generations) to demonstrate that the model provides an excellent fit to historical data. We also provide support for the Norton-Bass Model by fitting it to these same data.


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