Forecast quality improvement with Action Research: A success story at PharmaCo

There is a gap in the forecasting research surrounding the theory of integrating and improving forecasting in practice. The number of academically affiliated consultancies and knowledge transfer projects that there are around, due to a need for improvements in forecast quality, would suggest that many interventions and actions are taking place. However, the problems that surround practitioner understanding, learning and usage are rarely documented. This article takes the first step toward trying to rectify this situation by using the specific case study of a fully engaged company. A successful action research intervention in the Production Planning and Control work unit improved the use and understanding of the forecast function, contributing to substantial savings, enhanced communication and improved working practices.     

EMPIRICAL PERFORMANCE OF GARCH MODELS WITH HEAVY‐TAILED INNOVATIONS

We introduce a new type of heavy‐tailed distribution, the normal reciprocal inverse Gaussian distribution (NRIG), to the GARCH and Glosten‐Jagannathan‐Runkle (1993) GARCH models, and compare its empirical performance with two other popular types of heavy‐tailed distribution, the Student's t distribution and the normal inverse Gaussian distribution (NIG), using a variety of asset return series. Our results illustrate that there is no overwhelmingly dominant distribution in fitting the data under the GARCH framework, although the NRIG distribution performs slightly better than the other two types of distribution. For market indexes series, it is important to introduce both GJR‐terms and the NRIG distribution to improve the models’ performance, but it is ambiguous for individual stock prices series. Our results also show the GJR‐GARCH NRIG model has practical advantages in quantitative risk management. Finally, the convergence of numerical solutions in maximum‐likelihood estimation of GARCH and GJR‐GARCH models with the three types of heavy‐tailed distribution is investigated.     

Is it U.S. GAAP or IFRS? Understanding how R&D costs affect ratio analysis

While financial reporting standards under U.S. GAAP and IFRS are fundamentally similar, differences do exist that may affect our analysis of company financial statements. This is particularly true when comparing a U.S. company following U.S. GAAP to a firm that uses IFRS. To illustrate, we compare research and development (R&D) accounting methods under both sets of standards and illustrate how they affect the analysis of financial results of firms in a specific industry—automotive manufacturers. Our results provide insight into settings in which differences in R&D accounting may have the greatest impact on financial analysis.     

Cost comparison of continued anticoagulation with rivaroxaban versus placebo based on the 1-year EINSTEIN-Extension trial efficacy and safety results

Aims: The EINSTEIN-Extension trial (EINSTEIN-EXT) found that continued treatment with rivaroxaban for an additional 6 or 12 months (vs placebo) after 6–12 months of initial anticoagulation significantly reduced the risk of recurrent venous thromboembolism (VTE) with a small non-significant increased risk of major bleeding (none fatal or in critical site). This study aimed to compare total healthcare cost between rivaroxaban and placebo, based on the EINSTEIN-EXT event rates.

Methods: Total healthcare cost was calculated as the sum of treatment and clinical event costs from a US managed care perspective. Treatment duration and event rates were obtained from the EINSTEIN-EXT study. Adjustment on treatment duration was made by assuming a 10% non-adherence rate. Drug costs were based on wholesale acquisition costs. Cost estimates for clinical events (i.e. recurrent deep vein thrombosis [DVT], recurrent pulmonary embolism, major bleeding, clinically relevant non-major bleeding) were determined from the literature. Results were examined over a ±20% range of each cost component and over 95% confidence intervals (CIs) of event rate differences in deterministic (one-way) and probabilistic sensitivity analyses (PSA).

Results: Total healthcare cost was $1,454 lower for rivaroxaban-treated (vs placebo-treated) patients in the base-case, with a lower clinical event cost fully offsetting drug cost. The cost savings of recurrent DVT alone (–$3,102) was greater than drug cost ($2,723). Total healthcare cost remained lower for rivaroxaban in the majority (73%) of PSA (cost difference [95% CI]?=?–$1,454 [–$2,396, $1,231]).

Limitations: This study was conducted over the 1-year observation period of the EINSTEIN-EXT trial, which limited “real-world” applicability and examination of long-term economic impact. Assumptions on drug and clinical event costs were US-based and, thus, not applicable to other healthcare systems.

Conclusions: Total healthcare costs were estimated to be lower for patients continuing rivaroxaban therapy compared to those receiving placebo in VTE patients who had completed 6–12 months of VTE treatment.     

A REVIEW OF THE EMPIRICAL LITERATURE ON FARMER COOPERATIVES: PERFORMANCE,OWNERSHIP AND GOVERNANCE,FINANCE, AND MEMBER ATTITUDE

The empirical literature on farmer cooperatives is now fast emerging and developing in the areas of performance, ownership and governance, finance, and member attitude. We discuss 56 peer‐reviewed publications to illustrate the main findings and conclusions while outlining challenges and opportunities for future research. Generally, cooperative membership is found to positively impact price, yield, input adoption, income, and other indicators of member performance, yet there is growing evidence of an uneven distribution of benefits for small and large producers. In terms of structure, evidence of a causal relationship of ownership and governance to performance has been elusive, yet there are now many findings of inherent equity and long‐term debt constraints, often in the context of consolidation to drive scale and scope economies. Further inefficiency is observed to be driven by increased heterogeneity in member attitudes and objectives, in particular in terms of commitment and participation. Thus, overall, empirical work portrays farmer cooperatives as flawed and complex business organizations which nonetheless have a strong positive impact on its members. While applied research may progress in various directions, a general improvement in empirical methodologies is needed to allow robust analysis of mixed objectives in dynamic environments.     

An explorative study of corporate travellers’ perception at a German airport

The modern working environment is changing at a fast pace due to factors such as globalisation, digitalisation, and demographic trends. Taking an exploratory approach, this study examines how prevailing factors shaping the working world may influence the perception of business air travellers. Relevant factors are identified through a literature review, which results are confirmed by expert interviews (N = 11). Business travellers are surveyed (N = 67) at Munich Airport regarding their personal experiences and their evaluations of these identified factors. Their perceptions concerning the psychological and physical experience, digitalisation, age, and gender are examined in detail.Findings provide insights into the development of business air travel, with a focus on German business travellers. Despite the influence of advanced information and communications technology, survey results reveal that air travel might stay an essential part of the working world, as face-to-face meetings are not fully replaceable. Increasing multi-partner project work and flexible work structures could even lead into an increase of air travel. The study also delineates recommendations and research potential, such as the extension of the study in the light of the global COVID-19 pandemic. The question of how trends within the working world influence the perception of business related air travel is rarely studied. This study contributes to this gap in the scientific community.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

Bridging the great divide? Making sense of the human rights-CSR relationship in UK multinational companies

Human rights (HR) and corporate social responsibility (CSR) are both fields of knowledge and research that have been shaped by, and examine, the role of multi-national enterprises in society. Whilst scholars have highlighted the overlapping nature of CSR and HR, our understanding of this relationship within business practice remains vague and under-researched. To explore the interface between CSR and HR, this paper presents empirical data from a qualitative study involving 22 international businesses based in the UK. Through an analysis based on sensemaking, the paper examines how and where CSR and HR overlap, contrast and shape one another, and the role that companies’ international operations has on this relationship. The findings reveal a complex and multi-layered relationship between the two, and concludes that in contrast to management theory, companies have bridged the ‘great divide’ in varying degrees most notably in their implementation strategies.     

关于网络环境下工业工程应用研究的思考

分析传统IE应用现状 ,探讨国内企业与发达国家企业相比在传统IE应用方面存在差距的原因 ,提出缩小差距的解决方略 ,阐明网络环境下IE应用研究重点等。     

Effect Sizes in Qualitative Research: A Prolegomenon

The American Psychological Association Task Force recommended that researchers always report and interpret effect sizes for quantitative data. However, no such recommendation was made for qualitative data. Thus, the first objective of the present paper is to provide a rationale for reporting and interpreting effect sizes in qualitative research. Arguments are presented that effect sizes enhance the process of verstehen/hermeneutics advocated by interpretive researchers. The second objective of this paper is to provide a typology of effect sizes in qualitative research. Examples are given illustrating various applications of effect sizes. For instance, when conducting typological analyses, qualitative analysts only identify emergent themes; yet, these themes can be quantitized to ascertain the hierarchical structure of emergent themes. The final objective is to illustrate how inferential statistics can be utilized in qualitative data analyses. This can be accomplished by treating words arising from individuals, or observations emerging from a particular setting, as sample units of data that represent the total number of words/observations existing from that sample member/context. Heuristic examples are provided to demonstrate how inferential statistics can be used to provide more complex levels of verstehen than is presently undertaken in qualitative research.