The state of research on technological uncertainties, social uncertainties and emerging markets: A multidisciplinary literature review

The objective of this research work is to study the progress of research on technological uncertainties, social uncertainties and emerging markets and outline and identify the key disciplines, journals, articles and authors. For this the author studied the existing literature from the various fields in which technological uncertainties, social uncertainties and emerging markets research work have been published using ISI Web of Knowledge database. The paper finds that there is increasing research work on technological uncertainties, social uncertainties and emerging markets and the bibliographical search resulted in ninety-one documents written by one-hundred-sixty-one authors in eighty-four journals in seventy-two disciplines. The five major disciplines and their underlying journals are business and economics, agriculture, psychology, public administration, and environmental sciences and ecology accounting for majority of publications. In journals the most prolific, measured by number of articles published are Harvard Business Review, Social Science and Medicine, World Development, and Higher Education; and most influential, measured by the global citation received, are Harvard Business Review, Social Science and Medicine and Sociological Review. The top 10% of the journals are responsible for 23% of all publications but 85% of all global citations received. This highlights that despite the high, diverse and increasing number of journals; only few are dominating and shaping the research arena of technological uncertainties, social uncertainties and emerging markets. Further, in the ten most cited articles, no author appears more than once.     

Forecasting of electricity costs based on an enhanced gray-based learning model: A case study of renewable energy in Taiwan

This work presents a novel gray-based cost efficiency (GCE) model that integrates the gray forecasting model into a two-factor cost efficiency curve model for renewable energy (RE) technologies and identifies the optimal forecasting model for power generation cost of RE technologies. The analytical framework of proposed GCE model improves short-term prediction of power generation cost, and can be applied during the early developmental stages for RE technologies. Empirical analysis is based on wind power data for Taiwan. Time lag of knowledge stock was simulated to represent the actual relationship between R&D expenditures and cost reductions in power generation by knowledge stock. Analytical results demonstrate the GCE model is a useful tool to quantify the influences of cost reductions in power generation. The implications of analytical results are that institutional policy instruments play an important role in RE technologies achieving cost reductions and market adoption. The proposed GCE model can be applied to all high-technology cases, and particularly to RE technologies. The study concludes by outlining the limitations of the proposed GCE model and directions for further research.     

A grey decision and prediction model for investment in the core competitiveness of product development

Because enterprises do not disclose their internal specific cost information to the public and, moreover, every firm has its own product character and financial constitutions, it is difficult to offer fixed guidelines for investment decisions. Thus, an enterprise may be uncertain when required to choose the most promising set of possible investments.The goal of this research is to use a grey relation analysis and analytic hierarchy process (AHP) to probe the core product development and competitiveness of an enterprise from limited data and, furthermore, by constructing the grey model, GM(1,1), to validate the feasibility of this assessment of the core competitiveness and investment strategy. In this study, a precision mechanical manufacturer is taken as an example, and the forecast estimate from this method is compared to those of a linear regression and the actual values to demonstrate the feasibility of applying this methodology to investment decision making, hence, demonstrating the value of this research.     

Social media? Get serious! Understanding the functional building blocks of social media

Traditionally, consumers used the Internet to simply expend content: they read it, they watched it, and they used it to buy products and services. Increasingly, however, consumers are utilizing platforms—such as content sharing sites, blogs, social networking, and wikis—to create, modify, share, and discuss Internet content. This represents the social media phenomenon, which can now significantly impact a firm's reputation, sales, and even survival. Yet, many executives eschew or ignore this form of media because they don’t understand what it is, the various forms it can take, and how to engage with it and learn. In response, we present a framework that defines social media by using seven functional building blocks: identity, conversations, sharing, presence, relationships, reputation, and groups. As different social media activities are defined by the extent to which they focus on some or all of these blocks, we explain the implications that each block can have for how firms should engage with social media. To conclude, we present a number of recommendations regarding how firms should develop strategies for monitoring, understanding, and responding to different social media activities.     

Markets as networks: implications for strategy-making

Based on empirical studies of firm exchange activities in business markets, this paper outlines a business network view of the firm-market relationship, which differs fundamentally from the view assumed by neo-classical economic theory. We define business networks as sets of connected business relationships. Thus business relationships and connections between relationships are the critical elements in the business network view. It is assumed, as suggested by the Uppsala internationalization process model, that an interplay between knowledge and commitment development is the mechanism that drives the relationship and network development process. Against this background the paper discusses how strategic change is analyzed in literature on alliances and networks. In conclusion the paper presents a set of propositions about strategy-making in business network settings.     

Measuring risky adolescent cycling behaviour

Adolescents are at a greater risk of being involved in traffic accidents than most other age groups, even before they start driving cars. This article aims to determine the factor structure of a self-report questionnaire measuring adolescent risky cycling behaviour, the ACBQ (Adolescent Cycling Behaviour Questionnaire). The questionnaire's structure was based on the widely used Driver Behaviour Questionnaire (DBQ). A sample of secondary school students (N?=?1749; age range: 13-18 years) filled out the questionnaire. Factor analysis revealed a three-factor structure underlying the questionnaire, which was confirmed on two equally large portions of the entire sample. These three underlying factors were identified as errors, common violations and exceptional violations. The ACBQ is a useful instrument for measuring adolescents' risky cycling behaviour.     

Local institutions: Regulation and valuation of forest use—Evidence from Central Sulawesi,Indonesia

Forest management poses particular challenges as the pressure on forests is huge due to deforestation. In this context, the establishment of protected areas is a common conservation measure where institutions are put in place and sanctions regarding forest use are enforced. This paper focuses on the practice of sustainable forest management and the associated perspectives of local institutions at the rainforest margins of Lore Lindu National Park (LLNP) in Central Sulawesi, Indonesia.     

Learning patterns in early stage R&D projects: empirical evidence from the fibre raw material technology project in the Netherlands

Past research has reported that learning processes in early stage R&D are either chaotic, or absent. We challenge this finding by elaborating Van de Ven et al.’s trial‐and‐error learning model and explore an alternative conceptualization. We explored the combinations of positive and negative outcomes and action course continuation and modification. We use data gathered in an R&D setting of a 4‐years pre‐competitive knowledge generation project in the Dutch paper and board industry. Whereas the Van de Ven and Polley (1992) approach applied on our data also would lead us to conclude that ‘no learning’ would happen, our decomposed model identified three distinct learning patterns: (1) a virtuous pattern of positive outcomes resulting in continuations of action courses; (2) a vacuous pattern of negative outcomes resulting in modifications of action courses; and (3) a verification pattern of positive outcomes resulting in modifications of action courses. We observed the virtuous and verification patterns during the first 2 years and virtuous and vacuous learning in the second 2 years. These results might be useful for R&D managers since they provide insight into how an early stage R&D project can develop and where managers might intervene and adjust action courses.     

A Conjoint/Logit Analysis of Consumers’ Responses to Genetically Modified Tofu in Taiwan

We use data collected from a consumer survey of face‐to‐face interviews to determine consumer demand for genetically modified (GM) tofu attributes in Taiwan. Conjoint analysis using logit models reveals that, on average, brand is the most important attribute in terms of influence on consumers’ preferences, followed by price, with GM content having the least influence. However, the analysis also reveals three distinct market segments for tofu. Apart from the largest segment (which reflects the average lack of concern about GM food), the remaining two segments are split according to their preference or antipathy towards GM tofu. This result suggests that GM labelling is helpful to Taiwanese tofu consumers.