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Discusses the building of a prototype decision‐support system for a container transport company in the light of constraining factors which affect scheduling of trucks and vehicle routeing problems of various kinds. Considers the prototype’s data requirements and describes the information flow analysis, drawing conclusions and offering suggestions, before proceeding to model the problem as a vehicle routeing problem. Describes the development of an heuristic procedure and how it was tested and validated. Summarizes the benefits of the analysis and the prototype’s construction.

The purpose of this paper is to examine potential demand side management (DSM) programs in terms of their impacts to the overall economy in Thailand.

A multi‐sector computable general equilibrium (CGE) model of Thailand has been developed to accomplish the objectives of this study. The potential DSM program considered refers to replacement of less efficient electrical appliances with their efficient counterparts in the household sector in Thailand.

The study finds that the economy‐wide impacts of the DSM program (e.g., economic welfare, GDP, international trade) depend on three key factors: the project economics of the DSM option or the ratio of unit cost of electricity savings to price of electricity (CPR); the implementation strategy of the DSM option; and scale or size of the DSM option. This paper shows that the welfare impacts of the DSM programs would improve along with the project economics of the DSM programs. If the DSM program is implemented under the CDM, the welfare impacts would increase along with the price for certified emission reductions units. On the other hand, the welfare impacts would increase up to the optimal size or scale of the program, but would start to deteriorate if the size is increased further.

The welfare function considered in this paper does not account for benefits of local air pollution reductions. The study provides crucial insights on designing DSM projects in Thailand to ensure that DSM programs are beneficial for the economy as a whole.

Analyses of DSM options under the CDM using CGE models are not available in the literature. This is the first paper in this area.

This paper aims to investigate empirically the findings of an analytical impure public good model. The impure public good model described in this study allows for the application of different technologies generating public and private characteristics. The influence of the individual technologies on the total level of (impure) public good provision is of main concern in this study.

After the illustration of the impure public good model, the analytical results are compared to the results of a numerical approach based on climate policy in Germany.

The study shows that comparative static analyses do not always generate clear results. Therefore, the numerical approach is helpful to derive unambiguous results. The paper finds that technologies which exclusively generate private characteristics may have significant effects on total impure public good provision, since they may replace the private characteristics of the impure public good.

This paper provides useful information on the influence of the individual technologies on the total level of (impure) public good provision.

The purpose of this paper is to examine the influence of entrepreneurial orientation (EO) within the framework of the job demands-resources (JD-R) model.

The sample of N=597 white-collars in the German media and IT industry is drawn via the professional network XING. Cross-sectional mediator models are used to test the hypothesis.

The processes proposed by the JD-R model find empirical support. Job demands primarily cause exhaustion while job resources increase job satisfaction. Besides, job demands reduce job satisfaction and job resources lead to less exhaustion. An exception is found for cognitive workload which rather acts like a job resource. EO mediates these effects in a favorable way. High job resources foster EO, which in turn reduces exhaustion and enhances job satisfaction. For job demands, EO shows a negative mediation reducing the health-impairment process and increasing job satisfaction.

Future research should broach the issue of adverse effects related to extreme employee entrepreneurship and potential negative effects.

Supporting and supervising an EO may help employees to cope with modern job profiles in agile organizations.

The findings provide support for a favorable mediating role of an entrepreneurial personal resource within the JD-R model. This knowledge may be used to consider individual work orientations and to organize work in a “healthy” way.

This paper aims to explore ethnic minority women’s gendered perceptions and processes of agricultural innovation in the Northern uplands of Vietnam. The key research question asks how women develop innovations and learn new agricultural practices within patriarchal family structures.

In-depth interviews including life histories were conducted with 17 female and 10 male farmers from different socio-economic groups; participant observation and key informant interviews were also carried out.

Women’s innovation processes are deeply embedded in their positions as wives and daughters-in-law. Their innovation tends to be incremental, small-scale and less technological, and they use innovation networks of women rather than those of the formal agricultural institutions, including bringing innovation knowledge from their birth family to the patrilocal household. Unlike men’s perceived innovation, women’s innovation is strongly linked to small-scale entrepreneurship, and it is a powerful approach in the sense that it strengthens the position of women in their families while improving the household economy.

Identifying socially constructed innovation processes helps policymakers to rethink the introduction of ready-made innovation packages, both in terms of content and delivery, and to facilitate innovation for women, as well as men, in marginalized positions.

Understanding the gendered processes of innovation instead of measuring gender gaps in innovation outcomes sheds light on women’s interests and preferences, which can inform policies for supporting women’s innovation and thereby lead to social change, including gender equity.

This paper contributes to the understanding of gendered innovation processes and entrepreneurship associated with agriculture in rural areas in non-Western ethnic-minority contexts, which is an area that past and current research on entrepreneurship has relatively ignored.

The innovation creation literature primarily focuses on urban firms/regions or relies heavily on these data; less studied are rural firms and areas in this regard. The purpose of this paper is to employ a new firm-level data set, national in scale, and analyze characteristics that potentially influence innovation creation across rural and urban firms.

The authors use the 2014 National Survey of Business Competitiveness (NSBC) covering multiple firm-level variables related to innovation creation combined with secondary data reflecting the regional business and innovative environments where these firms operate. The number of patent applications filed by these firms measures their innovation creation, and the paper employs a negative binomial regression estimation for analysis.

After controlling for industry, county and state factors, rural and urban firms differ in their innovation creation characteristics and behaviors, suggesting that urban firms capitalize on their resources better than rural firms. Other major findings of the paper provide evidence that: first, for rural firms, the influence of university R&D is relevant to innovation creation, but their perception of university-provided information is not significant; and second, rural firms that are willing to try, but fail, in terms of innovation creation have a slight advantage over other rural firms less willing to take on the risk.

This paper is one of the first to analyze the 2014 NSBC, a firm-level national survey covering a wide range of innovation-related variables. The authors combine it with other regional secondary data, and use appropriate analytical modeling to provide empirical evidence of influencing factors on innovation creation across rural and urban firms.