Déjà lu: On the limits of data reuse across multiple publications

Scholars in our field, Operations and Supply Chain Management (OSCM), are under high pressure to show research productivity. At most schools, this productivity is measured by the number of journal articles published. One possible response to such pressure is to improve research efficiency: publishing more journal articles from each data collection effort. In other words, using one dataset for multiple publications. As long as each publication makes a sufficient contribution, and authors ensure transparency in methods and consistency across publications, generating more than one publication from one data collection effort is possible. The aim of this Notes and Debates article, however, is to draw attention to inappropriate reuse of empirical data in OSCM research, to explain its implications and to suggest ways in which to promote research quality and integrity. Based on two cases of extensive data reuse in OSCM, eighteen problematic practices associated with the reuse of data across multiple journal articles are identified. Recommendations on this issue of data reuse are provided for authors, reviewers, editors and readers.     

Technologies in caregiving: professionals’ strategies for engaging with new technology

This article explores the adoption of new technology in organisations that provide senior citizen care. Inspired by Niklas Luhmann’s systems theory, we study how technology reduces complexity by identifying client needs and ensuring predictability in service delivery. However, how technologies are adopted in practice is not determined by technology since it is also structured by care-workers' continuous decision-making. Against this backdrop, we explore how technologies alter the conditions for decision-making in two settings of elderly care, and we describe how care workers seek to adapt technologies to their practical needs as well as conception of care ethics. Developing a systems theory approach, the article eschews a priori assumptions of technological constraint on care-workers’ professional autonomy, offering a more open-ended exploration of diversified strategies for coping with new technology. Our case studies show that employees develop diversified strategies for technology adoption, including both non-usage, heated resistance, excessive embrace, and creative adaption.     

The impact of purchasing strategy-structure (mis)fit on purchasing cost and innovation performance

The organizational design literature strongly supports the notion of “structure follows strategy”, and suggests that a misfit between the two has a negative effect on performance. Building on this line of argument, we examine to what extent the (mis)fit between purchasing strategy and purchasing structure impacts purchasing performance. We focus on cost and innovation purchase category strategies, and examine how the deviation from an ideal purchasing structure defined along three dimensions (centralization, formalization, and cross-functionality) impacts purchasing performance. Analysing data collected from 469 firms in ten countries, we demonstrate that a strategy-structure misfit negatively impacts purchasing performance in both cost and innovation strategies. We also find that purchasing proficiency is a mediator in this relationship between misfit and performance. Our findings aid managerial decision making by empirically validating the necessity of having the right purchasing structure for successfully executing different purchasing strategies.     

Climate for conflict management,exposure to workplace bullying and work engagement: a moderated mediation analysis

The present study investigates a potential preventive factor in relation to workplace bullying. Specifically, we examine how climate for conflict management (CCM) may be related to less bullying, increased work engagement, as well as whether CCM is a moderator in the bullying engagement relationship. The study was based on a cross-sectional survey among employees in a transport company (N = 312). Hypotheses were tested simultaneously in a moderated mediation analysis which showed that bullying and job engagement were related (H1), CCM was related to less reports of bullying (H2), CCM was related to work engagement (H3) and that CCM was indirectly related to job engagement through bullying (H4), but only when CCM was weak (H5). That is, CCM moderated the relationship between bullying and work engagement in that this relationship only existed when CCM was low. The present study contributes to theory within this research field by showing that organizational measures may not only prevent bullying, but may also affect how employees react when subjected to bullying. Furthermore, the effect of climate in relation to bullying may be down to the narrow bandwidth facet of CCM. The study informs employers how they may act to prevent bullying while also reducing the potential negative outcomes of those cases of bullying that inevitably will show up from time to time.     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

Predicting the equity market with option-implied variables

We comprehensively analyze the predictive power of several option-implied variables for monthly S&P 500 excess returns and realized variance. The correlation risk premium (CRP) and the variance risk premium (VRP) emerge as strong predictors of both excess returns and realized variance. This is true both in- and out-of-sample. Our results also reveal that statistical evidence of predictability does not necessarily lead to economic gains. However, a timing strategy based on the CRP leads to utility gains of more than 5.03% per annum. Forecast combinations provide stable forecasts for both excess returns and realized variance, and add economic value.     

产研协同提高创新链整体效能的新探索 ——基于新型科研机构的考察

我国国家创新系统和公共研发体系在应对当前国际竞争中发挥了巨大作用,但也暴露出在基础研究—应用研究—试验开发创新链过度分工问题,使各创新主体脱节.定位于工业研究院的新型科研机构,在创新组织和成果转化中正在逐渐显露出独特的优势,成为提高创新链整体效能的重要突破口.中国科学院深圳先进技术研究院以科学技术为枢纽、以产业协同为触媒的"渡船模式",通过协同创新克服科研与产业之间的缺失环节,成为贯通创新链、提高创新链整体效能的有效路径之一.