Persistence Modeling for Assessing Marketing Strategy Performance

The question of long-run market response lies at the heart of any marketing strategy that tries to create a sustainable competitive advantage for the firm or brand. A key challenge, however, is that only short-run results of marketing actions are readily observable. Persistence modeling addresses the problem of long-run market-response quantification by combining into one measure of “net long-run impact†the chain reaction of consumer response, firm feedback and competitor response that emerges following the initial marketing action. In this paper, we (i) summarize recent marketing-strategic insights that have been accumulated through various persistence modeling applications, (ii) provide an introduction to some of the most frequently used persistence modeling techniques, and (iii) identify some other strategic research questions where persistence modeling may prove to be particularly valuable.long-run effectiveness;marketing strategy;time-series analysis

Persistence models and marketing strategy.

Marketing; Persistence; Models; Model; Strategy;

Data Analytics in Test: Recognizing and Reducing Subjectivity

Applying data analytics in production test has become a widely adopted industrial practice in recent years. As the complexity of semiconductor devices scales and the amounts of available test data continue to grow, the research direction in this field is forced to shift away from solving specific problems with ad hoc approaches and demands for deeper understanding of the fundamental issues. Two data-driven test applications where this shift is apparent are production yield optimization and defect screening, where the respective underlying data analytics approaches are correlation analysis and outlier analysis. A core issue present in these two approaches stems from the subjectivity that is inherent to data analytics. This dissertation delves into how subjectivity manifests itself and what can be done to reduce it with respect to the two test applications.Outlier analysis is an approach used for identifying anomalies. The main goal of outlier analysis in test is to capture statistically outlying parts with the hope that their abnormal behavior is attributed to some defectivity. During creation of an outlier model, the decisions about outlying behavior in the existing data are made by utilizing known failures and the test engineer's best judgment. In practice, outlier screening methods are simply used for transforming data into an outlier score space. Even if outlier analysis techniques are able to successfully classify a dataset into inliers and outliers, outlier models require thresholds to be decided. A concept called Consistency is introduced to provide an objective data-driven way to evaluate outlier models by utilizing all available data. The key observation underlying this concept is that outlier analysis should be immune to noise introduced by sources of systematic variation.Correlation analysis is a process comprising a search for related variables. The application of production yield optimization involves searching for correlation between the yield and various controllable parameters. The goal of this process is to uncover parameters that, when adjusted, can result in yield improvement. This analytics process is subjective to the perspective of the analyst and the quality of the result is highly dependent on the analyst’s previous experiences. In order to reduce the subjectivity in this application, a process mining methodology is introduced to learn from the experiences of analysts. The key advantage of this methodology is that in addition to having the capability to record and reproduce these analyses, it can also generalize to analytics processes not contained in the learned experiences

Setting network tariffs with heterogeneous firms: The case of natural gas distribution

The appropriate treatment of firm heterogeneity plays a crucial role in the application of benchmarking analyses for regulatory purposes. Within the realm of two-step approaches, this paper challenges the widespread adoption of single-variable clustering: heterogeneity has often multiple sources, which calls for more sophisticated clustering methodologies. In fact, reliable cluster-specific rankings provide firms’ management with more realistic objectives as well as freedom to identify the appropriate strategies to improve efficiency. In order to provide regulatory guidance on this issue, we use a unique dataset of detailed accounting data and unbundled network-related costs for a panel of Italian gas distributors and we test two alternative methods: a hybrid clustering procedure (HCP) and a latent class model (LCM). Our results show that HCP and LCM perform better than size segmentation in the identification of classes, thereby leading to more reliable production frontiers, but do not support a conclusive preference for one or the other method. While both methods are sensitive to outliers, LCMs seem to provide deeper insights on the drivers of firm inefficiency. However, they also present stationarity and convergence issues, which might favour the implementation of HCP methods. Furthermore, the degree of discretionary judgement in the modelling decisions (e.g., model specification and choice of the partition) is slightly higher with LCMs than with HCP. In this respect, the HCP, with its lower modelling and analytical complexity, may feature as a more appealing option, facilitating the interactions between regulator and firm managers

Islamic Ethical Leadership: Improving the Performance of Sharia Financial Institutions with CSR during the Covid 19 Pandemic

AbstractPurpose - This research was conducted with the aim of identifying the relationship between Islamic Ethical leadership on organizational performance with social responsibility as a mediation moderated by the covid 19 pandemic.Method - The research data were obtained from BMT Al-Amin located in Wonosobo Regency, Central Java Province. Samples were taken from the population using census sampling. Data collection is taken directly from the object of research through a questionnaire. Then the data were analysed by Structural Equation Modelling (SEM) with Amos software version 20.Result - From the research that has been done, it is found that Islamic Ethical leadership has an effect on organizational performance at BMT Al-Amin. CSR apparently does not mediate the relationship of Islamic Ethical leadership to organizational performance. And the COVID-19 pandemic has also not moderated CSR's relationship to organizational performance.Implication - This study uses data on BMT Al-Amin, Wonosobo Regency, Central Java Province.Originality- This paper looks at the relationship of ethical leadership to organizational performance with social responsibility as a mediation moderated by the covid 19 pandemic in order to support the creation of BMT growth in Wonosobo Regency during the covid 19 pandemic which is influenced by ethical leadership attitudes through CSR.

Islamic Ethical Leadership: Improving the Performance of Sharia Financial Institutions with CSR during the Covid 19 Pandemic

AbstractPurpose - This research was conducted with the aim of identifying the relationship between Islamic Ethical leadership on organizational performance with social responsibility as a mediation moderated by the covid 19 pandemic.Method - The research data were obtained from BMT Al-Amin located in Wonosobo Regency, Central Java Province. Samples were taken from the population using census sampling. Data collection is taken directly from the object of research through a questionnaire. Then the data were analysed by Structural Equation Modelling (SEM) with Amos software version 20.Result - From the research that has been done, it is found that Islamic Ethical leadership has an effect on organizational performance at BMT Al-Amin. CSR apparently does not mediate the relationship of Islamic Ethical leadership to organizational performance. And the COVID-19 pandemic has also not moderated CSR's relationship to organizational performance.Implication - This study uses data on BMT Al-Amin, Wonosobo Regency, Central Java Province.Originality- This paper looks at the relationship of ethical leadership to organizational performance with social responsibility as a mediation moderated by the covid 19 pandemic in order to support the creation of BMT growth in Wonosobo Regency during the covid 19 pandemic which is influenced by ethical leadership attitudes through CSR.

Forecasting: theory and practice

Forecasting has always been in the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organisations seeking to minimise risks and maximise utilities. The lack of a free-lunch theorem implies the need for a diverse set of forecasting methods to tackle an array of applications. This unique article provides a non-systematic review of the theory and the practice of forecasting. We offer a wide range of theoretical, state-of-the-art models, methods, principles, and approaches to prepare, produce, organise, and evaluate forecasts. We then demonstrate how such theoretical concepts are applied in a variety of real-life contexts, including operations, economics, finance, energy, environment, and social good. We do not claim that this review is an exhaustive list of methods and applications. The list was compiled based on the expertise and interests of the authors. However, we wish that our encyclopedic presentation will offer a point of reference for the rich work that has been undertaken over the last decades, with some key insights for the future of the forecasting theory and practice

Persistence Modeling for Assessing Marketing Strategy Performance

The question of long-run market response lies at the heart of any marketing strategy that tries to create a sustainable competitive advantage for the firm or brand. A key challenge, however, is that only short-run results of marketing actions are readily observable. Persistence modeling addresses the problem of long-run market-response quantification by combining into one measure of “net long-run impact” the chain reaction of consumer response, firm feedback and competitor response that emerges following the initial marketing action. In this paper, we (i) summarize recent marketing-strategic insights that have been accumulated through various persistence modeling applications, (ii) provide an introduction to some of the most frequently used persistence modeling techniques, and (iii) identify some other strategic research questions where persistence modeling may prove to be particularly valuable