Organizational attention and learning under regulatory intervention: Governmental investigation into auto engine quality

We examine the efficacy of government regulation on a firm's product. We draw on the behavioural approach of organization research in order to understand the micromechanisms whereby the regulatory intervention process affects corporate operation. We suggest that while government investigations may limit the improvements in product quality by distracting a firm's attention, this unintended outcome depends on the extent to which the firm engages in a substantive problem‐solving process with the regulator during an investigation process. A longitudinal analysis of the US government's investigation into motor vehicle engine production offers overall support for our argument. The paper concludes with a discussion of the implications that our findings present to learning theory and institutional literature. Copyright © 2017 ASAC. Published by John Wiley & Sons, Ltd.     

国内外社会资本与旅游研究文献综述

社会资本包含集体社会资本和个体社会资本。通过对Elsevier，Springer link和CNKI等平台上的文献进行梳理发现：在旅游领域，社会资本理论研究主要集中于集体和个体社会资本对旅游发展影响以及旅游对目的地社会资本影响等方面，研究呈现出内容上集中于社会资本对旅游的影响，方法上以案例分析为主的特点，当前仍存在不足，并提出今后研究的趋势，为以旅游创新助力乡村振兴，关注特色小镇发展模式，促进文化旅游可持续等，更好地运用社会资本理论来解释和解决旅游活动中的现象和问题，促进旅游业可持续发展。     

Problematizing socioemotional wealth in family firms: a systems-theoretical reframing

The concept of socioemotional wealth (SEW) seeks to present an independent paradigmatic basis for family-firm research, and in doing so aims to establish a sound basis for the scientific legitimacy of family-firm research. Establishing that legitimacy requires scholars to demonstrate that SEW is based on coherent assumptions on several theoretical levels. This paper uses the problematization methodology to challenge the coherence of the theoretical assumptions underpinning SEW and to advance theory development. The results of this problematization show that SEW is built on a theoretical level close to the object of research (in-house assumptions), but that more deeply-rooted theoretical levels (e.g. paradigmatic assumptions) are not sufficiently elaborated. Moreover, the original conceptualization is based on a positivist-mechanistic view, which hinders SEW reflecting the complex reality of family firms. Based on the results of this problematization, new systems theory is applied to reframe SEW’s theoretical grounding. Thereby the main contribution of the paper is a critical reflection on the theoretical underpinnings of SEW (in particular root-metaphor and paradigmatic assumptions), serving as the basis for advancing a coherent theoretical understanding of this important concept in family business research.     

Tourism and climate change: a review of threats and adaptation strategies for Africa

The intersection of tourism and climate change has seen significant research over the past two decades, focusing particularly on issues of mitigation and adaptation in the global North. Research output has predominantly been centred on the Mediterranean and Nordic countries and number of localities in North America. The global South has seen significantly less investigation, despite having significantly lower adaptive capacity to the impacts of climate change, and numerous countries with rapidly growing tourism sectors. The African continent specifically has seen appreciably less research than other countries in the global South, despite arguably having the lowest adaptive capacity and projections of severe impacts of climate change to the tourism sector from temperature increases, changes in precipitation volume and sea level rise. This paper therefore presents a review of the existing literature on adaptation strategies of tourism sectors and participants in African countries. The crucial argument of this paper is in highlighting the need for an increase in research into the threats of climate change to tourism in African countries, identifying future research trajectories. The development of such knowledge would assist in the development of adaptation and mitigation strategies for these most vulnerable tourism economies.     

Comparing automated text classification methods

Online social media drive the growth of unstructured text data. Many marketing applications require structuring this data at scales non-accessible to human coding, e.g., to detect communication shifts in sentiment or other researcher-defined content categories. Several methods have been proposed to automatically classify unstructured text. This paper compares the performance of ten such approaches (five lexicon-based, five machine learning algorithms) across 41 social media datasets covering major social media platforms, various sample sizes, and languages. So far, marketing research relies predominantly on support vector machines (SVM) and Linguistic Inquiry and Word Count (LIWC). Across all tasks we study, either random forest (RF) or naive Bayes (NB) performs best in terms of correctly uncovering human intuition. In particular, RF exhibits consistently high performance for three-class sentiment, NB for small samples sizes. SVM never outperform the remaining methods. All lexicon-based approaches, LIWC in particular, perform poorly compared with machine learning. In some applications, accuracies only slightly exceed chance. Since additional considerations of text classification choice are also in favor of NB and RF, our results suggest that marketing research can benefit from considering these alternatives.     

The impact of German-speaking online media on tourist arrivals in popular tourist destinations for Europeans

This empirical study analyzes the relationship between the sentiments in online media with regard to travel destinations and corresponding tourist arrivals. We expect the media reports on political and economic instability and turmoil to enhance tourist arrival nowcasts and forecasts, as they can probably complement them with information on disruptions and shocks. Therefore, we believe this research will help to build better models for tourism demand nowcasting and forecasting. We use the sentiment in the German-speaking online media because the German-speaking region is the most populated in Europe and has the largest group of travelers visiting destinations in and around Europe.

An artificial neural network is used to analyze the mood of the media. The software classifies news items regarding potential tourist destinations with either positive or negative labels. The number of positive and negative news items is used to build sentiment indices for popular tourist destinations for Europeans.

Our results show strong correlations between the mood concerning tourist destinations and tourist arrivals in these countries. Indeed, disruptions and shocks prevalent in the news are reflected in similar ratios in both tourist arrivals and sentiment indices. These results can be used as a new explanatory variable for tourism demand modelling.     

Pitching research: ‘qualitative cousins’ and the ‘extended family’

This study has two related goals – one very specific and one more general. The specific goal is to constructively engage with Lodhia (2017) on the issue of whether and to what extent ‘qualitative cousins’ are well served by Faff's (2015) original pitching research (PR) template. Using this ‘cousins’ focus as a primer, the more general goal is to update the agenda created by Faff (2015) and in so doing, explore the ‘extended family’ of PR work/resources now available.     

Drivers of research impact: evidence from the top three finance journals

We study the characteristics of all published papers in the top three finance journals (JF, JFE and RFS), and how these paper characteristics affect the number of citations in Google Scholar and the Web of Science database. First, we find the characteristics in the universalist perspective remain constant while the characteristics in the constructivist and presentation perspectives increase over time. Second, some characteristics are significantly different between the high-impact and the low-impact papers. Third, paper quality, research method, journal placement and paper age are the most important drivers. Last, different drivers play different roles in different journals.     

The role and impact of professional accountancy associations on accounting education research: An international study

This paper explores the relative influence of the accounting academy and accountancy professional associations in the debate concerning the profile and quality of accounting education research. This research analyses 13 semi-structured interviews undertaken with members of key accounting professional associations in Australia, New Zealand (ANZ) and the United Kingdom and Ireland (UKI). The paper makes a theoretical contribution by the novel application of the institutional logics theory to the literature concerning professional accounting associations (PAAs) demonstrating the dominant commercial logic of the education function and the more traditional fiduciary logic of the technical function. The research finds that the primary stakeholders in the professional accounting curriculum development model are the PAAs and employers, whilst the accounting academy is relatively absent. The relative independence of the education and research and technical functions within PAAs is also identified: academic research and technical activity has little influence on professional education and vice versa. However, PAAs’ funding of academic research is common across all four countries for brand recognition and in some instances to influence policy rather than informing the professional curriculum.