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Degradable mulch film (DMF) is a potential alternate to polyethylene (PE) mulching. In this regard, the purpose of this paper is to explore the effects and paths of natural disaster shock and risk aversion influencing farmers’ DMF adoption.

This research is conducted by collecting cross-sectional data of corn farmers in Zhangye, China. First, by using the Tobit model, the paper attempts to explore the effects of natural disaster shock and risk aversion influencing farmers’ DMF adoption. Second, IV-Tobit model is applied to deal with endogenous problems between risk aversion and DMF adoption. Additionally, the researchers used a moderating model to analyze feasible paths of natural disaster shock and risk aversion impacting farmers’ DMF adoption.

The outcomes show that natural disaster shock and risk aversion significantly and positively affect farmers’ DMF adoption. Though risk aversion plays a significant moderating effect in influencing farmers’ DMF adoption by natural disaster shock, the moderating effect has a serious disguising effect. By considering the heterogeneity of risk aversion, the paper further confirms that if the intensity of natural disaster shock is increased by one unit, the intensity of MDF adoption by farmers with high-risk aversion also tends to increase by 15.85%.

This study is the pioneer one, which is evaluating the intensity of farmers’ DMF adoption from adoption ratio, investment amount, labor input and adoption time. Additionally, the research provides important guidelines for policymakers to motivate medium and low-risk aversion farmers to adopt DMF.

The purpose of this paper is to describe and analyse a case of local freight stakeholder involvement to plan and design eco-efficient city logistics innovations in Como, a small city in Italy. While the importance of a well-functioning urban goods distribution system is widely acknowledged, city authorities have become increasingly aware of the need to minimise the negative impacts associated to the system. There are now countless examples of attempts to increase the eco-efficiency of urban freight deliveries; however, very few have made a notable impact. The success of such schemes often depends upon the response of a range of private sector freight stakeholders and their involvement during the planning process of these solutions is crucial.

To engage local freight stakeholders within the planning process of a city logistics project, the logical framework approach, in the form of the design and monitoring framework (DMF) developed by the Asian Development Bank, has been applied.

The structured consultation process implied within the DMF approach allowed urban freight stakeholders to share their aspirations from the beginning of the city freight planning process, despite their differences in priorities in adopting eco-efficient logistics innovations. The process ensured that city stakeholders accepted and committed to the city logistics strategies formulated during the consultation process, namely: changes to the Limited Traffic Zone regulation, the use of an urban consolidation centre and hybrid electric truck adoption.

The evaluation of the DMF application will be definitive after the demonstration/implementation stage of the city logistics project. It will then become clear if freight stakeholders have committed to the project and if it is effective in delivering the expected outputs and outcomes.

Local city authorities may find this method useful in situations where a structured consultation process is needed for addressing urban freight issues. This is especially the case in the context of introducing innovative, eco-efficiency solutions.

The application of DMF in the developed environment can be considered novel; this paper extends this with an application to the promotion of sustainable urban freight.

Documents a complex responsive process of profound organizational change taking place in a Dutch capital‐equipment manufacturing firm over a two‐year period beginning in September 1999. The primary focus of the initiative was on the transformation and development of the firm’s organizational mind – its “orgmind”. Although the company had an extensive history of system renewal activities, an evaluation of a decade of organization development efforts revealed that the “exterior” aspects of the system, e.g. tasks, structures, processes, tools, technology, etc., had received the bulk of attention. In contrast, the firm’s “interior”, consisting of such imperceptible qualities as the thoughts, beliefs, feelings and images held in the “mind” of the system, had been virtually ignored.

The purpose of this paper is to benchmark current adoption of green chemistry (GC) practices by the innovative and generic pharmaceutical companies and examine the drivers, barriers and future opportunities.

The authors examined publicly available data for the top 10 “big pharma” and top ten generic drug manufacturers. Using the IQ Green Chemistry working group framework for effective GC programs, they scored each of the 20 companies in seven key areas.

The study finds that generic drug companies have not embraced GC at the level of the innovative pharmaceutical companies (average GC score of 2 vs 11 for “big pharma”). Top two barriers for them include: lack of pressure and incentives, and the burdensome regulatory process for making changes in the manufacturing process.

The research is based on publicly disclosed information. It is possible that some generic drug manufacturers have begun to work internally on GC but have not disclosed externally yet. Future research should include a survey or interviews of generic drug manufacturers.

The company-level analysis, benchmarking framework and results are of value for researchers and practitioners interested in advancing greater adoption of GC by the pharmaceutical industry.

This study provides the first company-level benchmarking of GC adoption by the largest innovative and generics drug manufacturers. It contributes to the literature on the barriers and drivers for greater adoption of GC.

Modular integrated construction (MiC) is a modern construction method innovating and reinventing the traditional site-based construction method. As it integrates advanced manufacturing principles and requires offsite production of volumetric building components, several factors and conditions must converge to make the MiC method suitable and efficient for building projects in each context. This paper aims to present a knowledge-based decision support system (KB-DSS) for assessing a project’s suitability for the MiC method.

The KB-DSS uses 21 significant suitability decision-making factors identified through literature review, consultation of experts and questionnaire surveys. It has a knowledge base, a DSS and a user interface. The knowledge base comprises IF-THEN production rules to compute the MiC suitability score with the efficient use of the powerful reasoning and explanation capabilities of DSS.

The tool receives the inputs of a decision-maker, computes the MiC suitability score for a given project and generates recommendations based on the score. Three real-world projects in Hong Kong are used to demonstrate the applicability of the tool for solving the MiC suitability assessment problem.

This study established the complex and competing significant conditions and factors determining the suitability of the MiC method for construction projects. It developed a unique tool combining the capabilities of expert systems and decision support system to address the complex problem of assessing the suitability of the MiC method for construction projects in a high-density metropolis.

Pharmaceutical marketing, brand protection.

It could be used with the pharmaceutical marketing students and MBA students for analysing counterfeit medicines' menace in developing countries and positioning of a disruptive technology. The case could be used for marketing consultants, Brand managers and executive development programmes to explore issues such as protecting brands through technology, pharmaceutical packaging marketing, competitiveness of counterfeit drugs, global harmonisation.

Against the backdrop of rising menace of counterfeit drugs in developing countries, the case talks in particular about an innovative pharmaceutical packaging company. The company has developed a unique security technology called non-ClonableID™ which can enable products to be authenticated throughout the supply chain, thus protecting brands and preventing misuse. Despite a promising technology, it poses challenges regarding its adoption and commercial success.

Counterfeiting as an inevitable result of Globalization has become a global nuisance and has to be dealt at global level. Brand protection could be one of the lowest cost tools for pharmaceutical companies to restore public confidence in their products and themselves. While all methods for anti-counterfeiting are known to have short lives the menace still must be dealt with. For this, companies need to deploy anti-counterfeiting strategies that set up various layers of security.

Teaching note.

The purpose of this paper is to present the architectural principles and the services of the D-NET software toolkit. D-NET is a framework where designers and developers find the tools for constructing and operating aggregative infrastructures (systems for aggregating data sources with heterogeneous data models and technologies) in a cost-effective way. Designers and developers can select from a variety of D-NET data management services, can configure them to handle data according to given data models, and can construct autonomic workflows to obtain personalized aggregative infrastructures.

The paper provides a definition of aggregative infrastructures, sketching architecture, and components, as inspired by real-case examples. It then describes the limits of current solutions, which find their lacks in the realization and maintenance costs of such complex software. Finally, it proposes D-NET as an optimal solution for designers and developers willing to realize aggregative infrastructures. The D-NET architecture and services are presented, drawing a parallel with the ones of aggregative infrastructures. Finally, real-cases of D-NET are presented, to show-case the statement above.

The D-NET software toolkit is a general-purpose service-oriented framework where designers can construct customized, robust, scalable, autonomic aggregative infrastructures in a cost-effective way. D-NET is today adopted by several EC projects, national consortia and communities to create customized infrastructures under diverse application domains, and other organizations are enquiring for or are experimenting its adoption. Its customizability and extendibility make D-NET a suitable candidate for creating aggregative infrastructures mediating between different scientific domains and therefore supporting multi-disciplinary research.

D-NET is the first general-purpose framework of this kind. Other solutions are available in the literature but focus on specific use-cases and therefore suffer from the limited re-use in different contexts. Due to its maturity, D-NET can also be used by third-party organizations, not necessarily involved in the software design and maintenance.

The purpose of this paper is to investigate the determinants of marketing contract choices including written contracts, oral contracts and no contracts, as well as to examine the impact of marketing contracts on net returns from apple production in China.

A two-stage selection correction approach (Bourguignon, Fournier, and Gurgand (BFG)) for the multinomial logit model is employed to estimate the impact of marketing contracts on net returns from apple production. On the basis of the BFG estimation, the authors also use an endogenous switching regression model and a propensity score matching technique to estimate the causal effects of marketing contract choices on net returns from apple production.

The results reveal significant selectivity correction terms in the choices of both written contracts and no contracts and insignificant selectivity correction terms in the choice of oral contract, indicating that accounting for selection bias is a prerequisite for unbiased and consistent estimation. The findings also indicate written contracts increase apple farmers’ net returns, while oral contracts exert the opposite effect.

To the best of the authors’ knowledge, this study is the first to examine the impact of marketing contract choices on net returns from apple production, accounting for selectivity effects.

In this “Info-plosion” era, recommendation systems (or recommenders) play a significant role in finding interesting items in the surge of online digital activity and e-commerce. The purpose of this paper is to model users' preference evolution to recommend potential items which users may be interested in.

A novel recommendation system, namely evolution-learning recommendation (ELR), is developed to precisely predict user interest for making recommendations. Differing from prior related methods, the authors integrate the matrix factorization (MF) and recurrent neural network (RNN) to effectively describe the variation of user preferences over time.

A novel cumulative factorization technique is proposed to efficiently decompose a rating matrix for discovering latent user preferences. Compared to traditional MF-based methods, the cumulative MF could reduce the utilization of computation resources. Furthermore, the authors depict the significance of long- and short-term effects in the memory cell of RNN for evolution patterns. With the context awareness, a learning model, V-LSTM, is developed to dynamically capture the evolution pattern of user interests. By using a well-trained learning model, the authors predict future user preferences and recommend related items.

Based on the relations among users and items for recommendation, the authors introduce a novel concept, virtual communication, to effectively learn and estimate the correlation among users and items. By incorporating the discovered latent features of users and items in an evolved manner, the proposed ELR model could promote “right” things to “right” users at the “right” time. In addition, several extensive experiments are performed on real datasets and are discussed. Empirical results show that ELR significantly outperforms the prior recommendation models. The proposed ELR exhibits great generalization and robustness in real datasets, including e-commerce, industrial retail and streaming service, with all discussed metrics.

The purpose of this paper is to describe the evolution to date and future directions in research data policy, infrastructure, skills development and advisory services in an Australian university, with a focus on the role of librarians.

The authors have been involved in the development of research data services at Griffith, and the case study presents observations and reflections arising from their first-hand experiences.

Griffith University’s organisational structure and “whole-of-enterprise” approach has facilitated service development to support research data. Fostering strong national partnerships has also accelerated development of institutional capability. Policies and strategies are supported by pragmatic best practice guidelines aimed directly at researchers. Iterative software development and a commitment to well-supported enterprise infrastructure enable the provision of a range of data management solutions. Training programs, repository support and data planning services are still relatively immature. Griffith recognises that information services staff (including librarians) will need more opportunities to develop knowledge and skills to support these services as they evolve.

This case study provides examples of library-led and library-supported activities that could be used for comparative purposes by other libraries. At the same time, it provides a critical perspective by contrasting areas of good practice within the University with those of less satisfactory progress. While other institutions may have different constraints or opportunities, some of the major concepts within this paper may prove useful to advance the development of research data capability and capacity across the library profession.