Modelling Of Eco-innovation Diffusion: The EU Eco-label

The aim of this article is to carry out a theoretical and empirical analysis of the process of eco-label diffusion. Eco-labels allow consumers to identify products and services that have a reduced environmental impact during their life cycle. Thus, they are aimed at diminishing the information gap between sellers and buyers. The results of the estimation using the Bass model indicate that the diffusion of the EU eco-label has been most dynamic in countries such as Hungary, Poland, Denmark, Germany and France. In turn, the scope of diffusion (absolute saturation level) reached the highest value for companies in France and Italy. In addition, the results of the study confirm the stimulating impact of the scope of eco-label diffusion on consumer awareness of environmental issues. This finding points to the need for environmental education among consumers, which could in turn encourage firms to undertake pro-environmental actions

Modelling global diffusion.

This paper presents a general model of global diffusion processes. The approach recognizes 'breadth' and 'depth' of adoption by first considering the sequential introduction of the innovation across countries (breadth). Given the time of introduction into a specific country, within-country diffusion (depth) is subsequently modelled. We illustrate the approach using data from the cellular telephone industry for 184countries. The proposed provides empirical insights which could not have been obtained using traditional techniques. In particular, we show that breadth and depth processes are not necessarily affected by the same socioeconomic factors. We also are able to evaluate the importance of the linkage between the two processes.

The Role of Influentials in the Diffusion of New Products

This dissertation comprises three separate essays that deal with the role of influentials in the diffusion of new products. Influentials are a small group of consumers who are likely to play an important role in the diffusion of a new product through their propensity to adopt the product early and/or their persuasive influence on others’ new product adoption decisions. The literature labels these consumers as opinion leaders, social hubs, innovators, early adopters, lead users, experts, market mavens, and boundary spanners. This dissertation integrates two perspectives that researchers have mostly studied independently: market-level, which investigates the spread of a new product (e.g., total number of products sold) across markets over time as a function of aggregate-level marketing and social parameters; and individual-level, which considers how to identify influentials and their impact on the adoption behaviors of others. The first essay reviews and integrates the literature on the role of influentials in the diffusion of new products from a marketing management perspective. The study develops a framework using the individual- and market-level research perspectives to highlight five major interrelated areas: the two theoretical bases of why influentials have a high propensity to adopt new products early and why they considerably influence others’ adoption decisions, the issues concerned with how marketers can identify influentials and effectively target them, and how significant individual-level processes lead to significant market-level behavior. The study synthesizes the relevant research findings and suggests future research directions for improving our knowledge of the role of influentials in the diffusion of new products.The second essay explores firms’ decisions regarding the selection of target consumers for seeding—providing free products to enhance the diffusion process. The study examines the profit impact of targeting five groups of potential consumers for seeding under alternative social network structures. The findings suggest that seeding programs generally increase the net present value of profits. Moreover, social hubs—the most connected consumers—offer the best seeding target under most conditions that were examined. However, under certain conditions firms can achieve comparable results through random seeding and save the resources and effort required to identify the social hubs. Finally, the interactions among several variables—the choice of seeding target, consumer social network structure, and variable seeding cost—impact the returns that seeding programs generate and the ‘optimal’ number of giveaways.The third essay explores the adverse impacts of three types of consumer resistance to new products—postponement, rejection, and opposition—on firm profits. The study investigates these effects across five groups of consumers and alternative social network structures. The findings suggest that complex interactions between three groups of parameters—resistance, consumer social network, and diffusion parameters—affect the relationship between resistance and profits. Moreover, opposition reduces firm profits to a degree that is significantly greater than rejection and postponement. Finally, influential resister groups generally have stronger adverse impacts on profits than do randomly designated resisters

The adoption of lotteries in the United States, 1964 - 2007. A model of conditional and time-dynamical diffusion

The paper examines the determinants of the diffusion of state lotteries as a process of policy innovation. After more than 100 years of prohibition, U.S. states began to establish lotteries in the 1960s. The article uses statistical event history analysis to show that the adoption and diffusion of state lotteries depends on fiscal, political, and regional factors of competition as well as on normative factors of social legitimization. The article develops two further arguments, first by discussing an advanced model of regional diffusion that views the regional effect as being dependent on the ideologicalinstitutional context and second by analyzing time dynamics in the diffusion process to show how initial explanatory factors change over time. In general, the findings point to the institutional environment as a factor influencing the diffusion of organizations. -- Der Aufsatz beschäftigt sich mit den Determinanten der Diffusion staatlicher Lotterien als Beispiel einer politischen Innovation. Nach einer Verbotszeit von mehr als einhundert Jahren führten US-Bundesstaaten Lotterien ab den 1960er-Jahren schrittweise wieder ein. Anhand von statistischen Ereignisdatenanalysen zeigt der Beitrag, dass der Diffusionsprozess von fiskalischen, politischen und regionalen Faktoren ebenso wie von normativen Faktoren der sozialen Legitimierung abhängt. Der Aufsatz stellt zwei weitere Aspekte heraus, die empirisch demonstriert werden: Zum einen wird ein erweitertes regionales Diffusionsmodell diskutiert, das die räumliche Ausbreitung in Abhängigkeit zur ideologischen Struktur angrenzender Staaten erfasst; zum anderen wird die zeitliche Dynamik des Prozesses modelliert. Hierfür ist der soziologische Neo-Institutionalismus der theoretische Bezugspunkt, und es wird angenommen, dass mit zunehmender Dauer des Diffusionsprozesses die ursprünglichen Kausalfaktoren ihre Erklärungskraft zugunsten eines Bedeutungsgewinns von Legitimitätsaspekten verlieren. Die Ergebnisse dokumentieren isomorphische Adaptionsprozesse und in organisationsökologischer Hinsicht die Bedeutung institutioneller Umwelten für die Ausbreitung von Organisationen.

Cellular Automata with Network Incubation in Information Technology Diffusion.

Innovation diffusion of network goods determines direct network externalities that exhibit delayed full benefits, depressing sales for long periods. We model a multiplicative dynamic market potential driven by a latent heterogeneous individual threshold derived from a basic economic theory by Economides and Himmelberg (1995) which is embedded in a special Cellular Automata representation. The corresponding mean field approximation of its aggregate version is a Riccati equation with a closed form solution. This allows the detection of a change-point time separating an incubation period from a subsequent take-off due to a sufficient critical mass acting as a collective threshold. Weighted nonlinear least squares methodology is the main inferential technique. An application is analysed with reference to USA fax machine diffusion

Agroforestry Adoption in Ethiopia: Innovation Systems and Farm Level Analysis

Agroforestry (AF) or agroforestry innovation (AFI) production has long been and continues to be a component of the mixed farming system of Ethiopian and smallholder farmers worldwide. Interventions continue introducing new or improved management practices, species, and techniques to raise AFI's livelihood and natural resource management contributions. Despite considerable efforts, the adoption of these AFI continues to be limited, as proved by several adoption studies and development efforts. Formal and informal studies were conducted for decades to understand the problems for the low adoption of various AFI. Nevertheless, these studies generated redundant and marginally growing important information as it has weakly altered the course of development approaches and policy regulations. Learning from previous studies, researchers have been requesting more robust studies that help address existing knowledge gaps on adopting AFI. To respond to these calls, this PhD project examined the factors affecting the adoption of AFI by smallholders and Ethiopian farmers as a case study. The project builds upon previous studies to explore the diverse perspectives that influence the adoption of AFI. Literature assessment of recent studies indicated that several factors belonging to farmers and institutions influence the adoption of AFI. Simultaneously, we discovered that some issues were explored frequently (e.g., socioeconomic factors), whereas others (e.g., psychological factors) were largely ignored. Besides, researchers have followed the static assumption (i.e., adopt or non-adopt) and failed to learn the adoption process beyond a one-time decision. Additionally, the studies focused on discrete factors and activities and failed to comprehend the diverse perspectives and factors and their combined effect on eventual AFI adoption. Ultimately, learning from the larger adoption science and previous studies, we developed a comprehensive framework, 'AFI adoption framework' (chapter 4.1), that supports the meaningful assessment of adoption practices and comprehensively discovers factors influencing AFI adoption. The framework encompassed three compartmentalized and yet interlinked components that influence AFI adoption under smallholder contexts. The framework commended both distinct studies for exhaustive elaboration and simultaneously suggested holistic examination. Besides, it recommended minor and major modifications to the research approaches, such as proper treatment of variables in econometric models, incorporation of variables related to the psychological status, and employment of robust tools such as the real-options approach for profitability analysis. Based on this framework, we designed a project and conducted fieldwork in the Amhara region of Ethiopia, a typical smallholder context. We explored the household contexts (i.e., farm level and psychological), system level features, and innovation characteristics influencing smallholders' AFI adoption decisions. It employed mixed conventional and advanced analytical tools comprising content analysis, econometric models, principal component analysis, and financial discounting methods. Advanced methods comprehend process analysis and adoption dynamism. The results from discrete analysis indicated that socioeconomic factors, psychological constructs, system level features, and innovation attributes influence AFI adoption. Regarding innovation characteristics, the different attributes are foundations for undertaking AFI adoption decisions of smallholder farmers. Beyond adopt-non-adopt concepts, we found farmers continuously undertake follow-up adoptions of varying extents such as reduced, maintained, and increased. Based on our query and comparable to existing frameworks, the newly developed 'AFI adoption framework' is more reasonable to meaningfully investigate factors influencing AFI (and agricultural innovations) adoption under smallholder contexts. However, there is a need for precaution while employing the framework to more clearly discern the adoption process and reflect the integration among the factors and activities involved from the development to the adoption of AFI. This dissertation excluded empirical analysis of profitability and holistic assessment due to the voluminous nature of the dissertation.:PREFACE ii ACKNOWLEDGEMENTS iii SUMMARY iv ZUSAMMENFASSUNG vi LIST OF FIGURES ix LIST OF TABLES xi ACRONYMS xi 1. INTRODUCTION 1 1.1. Agroforestry in Ethiopia 1 1.2. Problem statement 4 1.3. Objectives and research questions 6 1.4. Scope of the study 7 1.5. Dissertation structure 8 2. CONCEPTUAL FRAMEWORK 11 2.1. The adoption concept 11 2.2. Theoretical frameworks on adoption 12 2.3. The critique and research context 16 2.4. The AFI adoption analytical framework 17 2.5. Description of links between objectives and research questions 19 3. RESEARCH METHODOLOGY 21 3.1. Description of the study area 21 3.2. Selection of innovations and farmers 22 3.3. Research methods 23 3.3.1. Data collection methods 23 3.3.2. Sampling technique and sample size 24 3.3.3. Data analysis 25 4. RESULTS 26 4.1. Agroforestry adoption as a systems concept: a review 27 4.2. Can a sequential analysis provide a more robust understanding of farmers’ adoption decisions? an example from an agroforestry adoption study in Ethiopia 58 4.3. Farmers’ intentions towards sustained agroforestry adoption: an application of the theory of planned behavior 88 4.4. Adoption under the influence of innovation attributes: the case of agroforestry innovations from Ethiopia 111 4.5. Influence of system level factors on adoption of agroforestry innovations 141 5. SYNTHESIS and CONCLUSION 170 5.1. Synthesis of key findings 170 5.1.1. State of AFI adoption research in SSA 170 5.1.2. Persistent calls for rigorous research 172 5.1.3. Critical factors affecting AFI adoption 173 5.1.4. Conceptualizing adoption as a complex decision process 175 5.2. Reflections on research method, theoretical framework, and generalization 177 5.2.1. Reflection on research methods and analytical generalization 177 5.2.2. Reflection on the theoretical framework and theoretical contribution 179 5.3. Outlook and suggestions 184 5.4.1. Recommendations for future research 185 5.4.2. Development and policy recommendations 186 5.5. Limitations of the study 186 REFERENCES 187 APPENDICES 19

Patterns In The Diffusion Of Strategies Across Organizations: Insights From The Innovation Diffusion Literature

Firms often adopt strategies in spite of mixed evidence about the strategy's performance and of evidence that the strategy leads to inefficient outcomes. Here, we describe the conditions prompting the spread of inefficient strategies through a population of firms, as well as the characteristics of individual firms that affect their propensity to adopt efficient and inefficient strategies. We focus on one pattern that appears common to strategic adoptions: a pattern where the number of unsuccessful adoptions exceeds the number of successful adoptions. We note how the failure to consider diffusion patterns in empirical strategic research limits use of that research as a source of prescriptive theory

Comparing adoption patterns: a global approach.

New product diffusion models are 'risky and potentially misleading' (Simon 1994, p. 14). This paper proposes a method which overcomes a number of problems associated with new product diffusion models noted in the marketing literature. We illustrate the methodology in the context of better understanding global variances in new product adoption. Building on existing diffusion models and sample matching principles from international consumer research, we suggest a 'staged estimation procedure'. The procedure provides both 'sensible' and robust estimates, and remains implementable even if the diffusion process is in its earliest stage in most or all countries. In an empirical illustration covering 184 countries on five continents, we use cellular diffusion data to gain insights on how exogenous/endogenous country characteristics affect country-level diffusion patterns.

Higher education technological knowledge and patterns of technology adoptions in undergraduate STEM courses

Identifying, examining, and understanding faculty members’ technological knowledge development and the process of technology adoption in higher education is a multifaceted process. Past studies have used Rogers (1995, 2003) diffusion of innovation theoretical framework to delineate the technology adoption process. These studies, however, have frequently reported the influencing factors based on the statistical analysis such as regression analysis-based approach, and have not focused on the emerging process of technology adoptions or the developing process of technological knowledge and pedagogical knowledge. A mixed method study was designed to see how faculty members acquire different technologies and develop technological knowledge that might help them adopt technologies in their classrooms and online using different pedagogies. A sample of STEM teaching faculty members with different ranks, tenure, teaching experience, and varied degree of experience in the use of educational technologies participated in the study. A survey was designed to identify internal and external factors affecting technology adoption and its effective use in different teaching activities. To elaborate survey results, the study also included class observations as well as pre- and post-observation interviews. Online classrooms used by the faculty via Blackboard learning management system, online flipped classrooms, or other websites such as Piazza were also examined for data triangulation. The findings of the study indicate that faculty members are influenced by their own professional motivations and student learning to improve their teaching methods and to enhance student interactions and learning through the use of different educational technologies. The adoption process was identified as spreading over a period of time and it looked at how faculty members’ developed their technological knowledge and pedagogical knowledge. With the recognition of the social, organizational, and professional motivational factors both expert faculty members, university administrators, and technologist could be made aware of the critical components necessary to construct and support a bottom-up or user-centric successful innovation adoption decision process. The bottom-up approach would use expert professors as change agents and educational designers that would encourage exchanges and meaningful dialogues about educational technology adoptions and effective uses of technology with pedagogy within each discipline and department