Towards a resilience management framework for complex enterprise systems upgrade implementation

The lack of knowledge of how resilience management supports enterprise system (ES) projects accounts for the failure of firms to leverage their investments in costly ES implementations. Using a structured-pragmatic-situational (SPS) case study research approach, this paper reports on an investigation into the resilience management of a large utility company as it implemented an ES upgrade. Drawing on the literature and on the case study findings, we developed a process-based resilience management framework that involves three strategies (developing situation awareness, demystifying threats, and executing restoration plans) and four organisational capabilities that transform resilience management concepts into practices. We identified the crucial phases of ES upgrade implementation and developed indicators for how different strategies and capabilities of resilience management can assist managers at different stages of an ES upgrade. This research advances the state of existing knowledge by providing specific and verifiable propositions for attaining a state of resilience, the knowledge being grounded in the empirical reality of a case study. Moreover, the framework offers ES practitioners a roadmap to better identify appropriate responses and levels of preparedness.     

A gossip based information fusion protocol for distributed frequent itemset mining

The computational complexity, huge memory space requirement, and time-consuming nature of frequent pattern mining process are the most important motivations for distribution and parallelization of this mining process. On the other hand, the emergence of distributed computational and operational environments, which causes the production and maintenance of data on different distributed data sources, makes the parallelization and distribution of the knowledge discovery process inevitable. In this paper, a gossip based distributed itemset mining (GDIM) algorithm is proposed to extract frequent itemsets, which are special types of frequent patterns, in a wireless sensor network environment. In this algorithm, local frequent itemsets of each sensor are extracted using a bit-wise horizontal approach (LHPM) from the nodes which are clustered using a leach-based protocol. Heads of clusters exploit a gossip based protocol in order to communicate each other to find the patterns which their global support is equal to or more than the specified support threshold. Experimental results show that the proposed algorithm outperforms the best existing gossip based algorithm in term of execution time.     

State of the art in business analytics: themes and collaborations

In this study, we illustrate the most recent stage in the scholarly development of the field of Business Analytics. Using around 23,000 research publications collected from the Web of Science, we network-analyzed four types of dataset that include keywords, titles, institutions, and countries. It is noteworthy that we found a thematic cluster focusing on analytical techniques and tools, particular with the rapid dissemination of “big data”-related studies. It is not surprising that universities and institutions in advanced countries in the West still occupy the central position of the collaboration network. However, we can discern a global shift toward certain developing and transitional economies in the world science base.     

The Relationship Between Consumer-Brand Identification and Brand Extension

The present research aims at examining the role of consumer-brand identification (CBI) in attitude toward brand extension regarding the congruency between the values of consumers and brands. In this way, the benefits of CBI to consumers and brand managers are outlined. This research has been conducted through designing a survey and collecting data through a questionnaire. For data mining and investigating the model, the SEM approach is implemented. According to the findings, high levels of CBI lead to positive attitudes toward the brand extension, and that value congruity positively impacts this relationship. The results outline that CBI impacts fit and tie in separate ways, so that CBI effect on fit is more substantial. Furthermore, according to the results, in comparison to the role of tie, the role of fit is more significant in predicting attitudes toward brand extension. The sample from university students is appropriate for testing theory, but limits generalizing the results of the research. In addition, this research has studied one product category and is limited in this perspective. The findings have remarkable recommendations for implementing brand extension as they emphasize the role of perceived fit. Moreover, by reexamining CBI in a less known market, the research has outlined its positive outcomes for firms. This research has used perceived tie in a brand extension context and, similar to perceived fit, has implemented it as another factor to predict attitude toward brand extension. In addition, this research is unique, as it has investigated CBI in a new context.     

How successfully China has applied the OECD principles of corporate governance: a critical assessment

This paper attempts to critically analyze how successful China has been in applying the OECD principles of corporate governance. In doing so, assessment has been made in light of the six core issues of the OECD principles. A satisfactory level of progress has been noted in China’s legal and regulatory framework since the 1990s. New laws, regulations, and rules have been enacted, existing ones have been amended, and all the required institutions have been built accordingly in order to ensure good corporate governance practices in the country. However, there are still bottlenecks in terms of the enforcement of these laws, regulations, and rules mainly due to the various structural limitations in the Chinese administration and judiciary. The paper argues that China should now move forward with an accelerated enforcement agenda in the area of corporate governance in order to make China Inc. more competitive and sustainable.     

Shrinkage Estimation Strategies in Generalised Ridge Regression Models: Low/High-Dimension Regime

In this study, we suggest pretest and shrinkage methods based on the generalised ridge regression estimation that is suitable for both multicollinear and high-dimensional problems. We review and develop theoretical results for some of the shrinkage estimators. The relative performance of the shrinkage estimators to some penalty methods is compared and assessed by both simulation and real-data analysis. We show that the suggested methods can be accounted as good competitors to regularisation techniques, by means of a mean squared error of estimation and prediction error. A thorough comparison of pretest and shrinkage estimators based on the maximum likelihood method to the penalty methods. In this paper, we extend the comparison outlined in his work using the least squares method for the generalised ridge regression.     

Explaining International Differences in Genetically Modified Food Labeling Policies*

Many countries have adopted labeling policies for genetically modified (GM) food, and the regulations vary considerably across countries. We evaluate the importance of political‐economic factors implicit in the choice of GM food labeling regulations. Using an analytical model, we show that production and trade‐related interests play a prominent role in labeling decision‐making. This conclusion is validated by an empirical analysis of GM food labeling policy choices. We find that countries producing GM crops are more likely to have less stringent labeling policies. Food and feed exporters to the European Union (EU) and Japan are more likely to have adopted stricter labeling policies. Labeling regulations in Asia and Europe are similar to those of Japan and the EU. Countries with no labeling policies are less developed, with important rural sectors and are more likely to have ratified the Cartagena Protocol on Biosafety.     

Democracy and environmental quality

We develop and estimate an econometric model of the relationship between several local and global air pollutants and economic development while allowing for critical aspects of the socio-political-economic regime of a State. We obtain empirical support for our hypothesis that democracy and its associated freedoms provide the conduit through which agents can exercise their preferences for environmental quality more effectively than under an autocratic regime, thus leading to decreased concentrations or emissions of pollution. However, additional factors such as income inequality, age distribution, education, and urbanization may mitigate or exacerbate the net effect of the type of political regime on pollution, depending on the underlying societal preferences and the weights assigned to those preferences by the State.