Computational Modeling of Culture's Consequences

This paper presents an approach to formalize the influence of culture on the decision functions of agents in social simulations. The key components are (a) a definition of the domain of study in the form of a decision model, (b) knowledge acquisition based on a dimensional theory of culture, resulting in expert validated computational models of the influence of single dimensions, and (c) a technique for integrating the knowledge about individual dimensions. The approach is developed in a line of research that studies the influence of culture on trade processes. Trade is an excellent subject for this study of culture’s consequences because it is ubiquitous, relevant both socially and economically, and often increasingly cross-cultural in a globalized world

Situated cognition and the culture of learning

Includes bibliographical references (p. 16-17

A Virtual Laboratory for the Study of History and Cultural Dynamics

This article presents a Virtual Laboratory that enables the researcher to try hypothesis and confirm data analysis about different historical processes and cultural dynamics. This Virtual Cultural Laboratory (VCL) is developed using agent-based modeling technology. Individuals' tendencies and preferences as well as the behavior of cultural objects in the transformation of cultural information are taken into consideration. In addition, the effect of local interactions at different scales over time and space is visualized through the VCL interface. Information repositories, cultural items, borders, population size, individual' tendencies and other features are determined by the user. Finally, the researcher can also isolate specific factors whose effect on the global system might be of interest to the researcher. All the code can be found at http://projects.cultureplex.ca/Cultural Dynamics, Cultural Complexity, Multi-Agent Based Simulation, Netlogo, Virtual Laboratory

Management control system : its antecedents and consequences on organizational performance

The purpose of this study was to examine the antecedents and consequences of Management Control System (MCS) in the context of a less-developed country. Based on contingency and resource-based view theories, the study examined whether perceived environmental uncertainty (PEU) (i.e., competitive, operational, political, and technological uncertainty), and national culture (i.e., high uncertainty avoidance, collectivism, and high-power distance), have significant influence on MCS represented by levers of control (i.e., beliefs, boundary, diagnostic, and interactive control) among firms listed on the Palestinian Securities Exchange. This study also examined whether MCS influenced organizational learning, the impact of organizational learning on organizational performance, and finally the mediating role of the organizational leaning between MCS and organizational performance. The sample framework was the entire population of the Palestinian firms listed on the Palestine Securities Exchange, which comprised 49 companies distributed into five different industries. Data were collected via survey questionnaires distributed to the top management and were analyzed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings indicated that PEU and national culture had a significant and positive influence on MCS. In addition, MCS also significantly influenced organizational learning. Furthermore, a significant positive association existed between organizational learning and organizational performance. Finally, the results indicated that organizational learning partially mediated the relationship between MCS and organizational performance. To conclude, this study has provided important insights on the factors influence MCS and its consequences on organizational performance in general, and specifically in Palestine. The findings contribute to the theoretical, methodological and practical and opened up possibilities for further research regarding MCS practices in Palestine and other developing countries, and worldwide

Factors Influencing Online Shopping Behavior Among Jordanian Academicians

Although online shopping had been widely adopted in developed countries, there was still low percentage of online shopping in developing countries like Jordan. The aims of this quantitative research were to empirically determine the significant predictors of online shopping behaviors (actual, intention and trust), examine the mediating effect of trust and intention on the relationship between predictors and actual online shopping behavior, and investigate the applicability of Theory of Planned Behavior (TPB) in explaining online shopping behavior in Jordan. A survey was conducted among 317 academic staff in ten universities located in three areas (North, Middle and South) in Jordan. Data were analyzed using Structural Equation Modeling (SEM). Out of 15 hypotheses of online shopping behaviors, nine had significant direct effects (intention, trust and subjective norm to actual behavior; trust, uncertainty avoidance, subjective norm and perceived behavior control to intention; uncertainty avoidance and subjective norm to trust). The study also found that intention was a fill mediator of the relationship between uncertainty avoidance and perceived behavioral control with actual online shopping behavior. It was found to be a partial mediator of the relationship between trust and subjective norm with actual online shopping behavior. Trust was also found as a fill mediator of the relationship between uncertainty avoidance and attitude with actual online shopping behavior. Finally, trust and intention filly mediated the relationship of uncertainty avoidance and attitude with actual online shopping behavior. The present study also highlighted implications of the study, future research work as well as its study limitations

The influence of national culture on the attitude towards mobile recommender systems

This is the post-print version of the final paper published in Technological Forecasting and Social Change. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.This study aimed to identify factors that influence user attitudes towards mobile recommender systems and to examine how these factors interact with cultural values to affect attitudes towards this technology. Based on the theory of reasoned action, belief factors for mobile recommender systems are identified in three dimensions: functional, contextual, and social. Hypotheses explaining different impacts of cultural values on the factors affecting attitudes were also proposed. The research model was tested based on data collected in China, South Korea, and the United Kingdom. Findings indicate that functional and social factors have significant impacts on user attitudes towards mobile recommender systems. The relationships between belief factors and attitudes are moderated by two cultural values: collectivism and uncertainty avoidance. The theoretical and practical implications of applying theory of reasoned action and innovation diffusion theory to explain the adoption of new technologies in societies with different cultures are also discussed.National Research Foundation of Korea Grant funded by the Korean governmen

Sales Growth of New Pharmaceuticals Across the Globe: The Role of Regulatory Regimes

Prior marketing literature has overlooked the role of regulatory regimes in explaining international sales growth of new products. This paper addresses this gap in the context of new pharmaceuticals (15 new molecules in 34 countries) and sheds light on the effect regulatory regimes have on new drug sales across the globe. Based on a time-varying coefficient model, we find that differences in regulation substantially contribute to cross-country variation in sales. One of the regulatory constraints investigated, i.e. manufacturer price controls, has a positive effect on drug sales. The other forms of regulation such as restrictions of physician prescription budgets and the prohibition of direct-to-consumer advertising tend to hurt sales. The effect of manufacturer price controls is similar for newly launched and mature drugs. In contrast, regulations on physician prescription budget and direct-to-consumer advertising have a differential effect for newly launched and mature drugs. While the former hurts mature drugs more, the latter has a larger effect on newly launched drugs. In addition to these regulatory effects, we find that national culture, economic wealth, introduction timing, lagged sales and competition, also affect drug sales. Our findings may be used as input by managers for international launch and sales decisions. They may also be used by public policy administrators to compare drug sales in their country to other countries and to assess the role of regulatory regimes therein.economics;regulation;culture;drug;international new product growth;penalized splines;pharmaceutical;timevarying effects

Інтелектуальний аналіз даних у дослідженні корпоративної культури підприємства

Обґрунтовано актуальність дослідження питання інтелектуального підходу до проведення аналізу діяльності під-приємства зважаючи на складність, мінливість, неоднозначність середовища, у якому працюють підприємства для з’ясування причинно-наслідкових зав’язків поточної ситуації та прогнозування її наслідків в майбутньому. Розглянуто основні шляхи проведення інтелектуального аналізу даних, зокрема статистики, штучного інтелекту та їх поєднан-ня. Охарактеризовано основні категорії проведення інтелектуального аналізу даних на основі виділення описового інтелектуального аналізу даних і прогнозного інтелектуального аналізу даних. Зокрема, охарактеризовано описовий інтелектуальний аналіз даних, який досліджує закономірності опису даних, та прогнозний інтелектуальний аналіз даних, що прогнозує поведінку моделі на основі доступного набору даних. Проведено дослідження структури та ме-тодів інтелектуального аналізу даних. Визначено, що інтелектуальний аналіз даних має велике значення в діловій та науковій сферах. Зазначено, що інтелектуальний аналіз даних, складається з пошуку, аналізу та сортування великих обсягів даних, з метою виявлення нових закономірностей, тенденцій розвитку та взаємозв'язку, що містяться в зі-браних даних. Охарактеризовано, що з огляду на величезну кількість даних, що зберігаються в файлах, базах даних та інших репозиторіях, важливим є володіння предметною сферою, яка потребує отримання нових знань із наявного набору даних, які могли б допомогти у прийнятті рішень. Виділено, що генерація даних і методів їх опрацювання для інтелектуального аналізу даних є важливим завданням і вимагає знання предметної області. Проведено інтелек-туальний аналіз для оцінки корпоративної культури промислових підприємств із використанням описового методу. Враховуючи складність досліджена феномену корпоративної культури на підприємствах та необхідність доповнення кількісних оцінок результатами проведених опитувань, які складно опрацьовувати традиційними статистичними ме-тодами, підсумовано, що інтелектуальний аналіз даних доцільно застосовувати для дослідження стану корпоратив-ної культури на підприємстві із виділенням її суттєвих атрибутів та їх характеристик, що впливають на діяльність підприємства загалом. Зроблено висновок, що в умовах розширення інформаційного поля у діяльності підприємств, зростатиме зв'язок управлінської діяльності із сферою інформаційних технологій.The relevance of the intellectual approach study to the analysis of the enterprise activity at conditions of complexity, vari-ability, ambiguity of the environment in which enterprises operate, in order to clarify the causal connections of the current situation and predict its consequences in the future, is justified. The main ways of data mining, in particular statistics, artificial intelligence and their combination are considered. The main categories of data mining based on the selection of descriptive data mining and predictive data mining are characterized. In particular, descriptive data mining that is used to examine the patterns of data description, and predictive data mining - to predict the behaviour of the model based on the available data set, are char-acterized. The structure and methods of data mining are investigated. It’s determined that data mining has a great importance in business and science. It’s noted that data mining consists of searching, analysing and sorting large amounts of data in order to identify new patterns, development trends and relationships contained in the collected data. It is described that given the huge amount of data stored in files, databases and other repositories, it is important to have a subject area that requires new knowl-edge from the existing data set that could help in decision making. It is highlighted that the generation of data and methods of their processing for data mining is an important task and requires knowledge of the subject area. The intellectual analysis for an estimation of corporate culture of the industrial enterprises with use of a descriptive method was carried out. Given the com-plexity of the studied phenomenon of corporate culture in enterprises and the need to supplement quantitative assessments of the results of surveys, which are difficult to process traditional statistical methods, it is concluded that data mining should be used to study the state of corporate culture in the enterprise. It is concluded that in the conditions of expansion of the information field in the activity of enterprises, the connection of managerial activity with the sphere of information technologies will grow

Examining Interactions in Social Network Sites through the Lense of Social Capital.

Rapid growth of the Internet has led to the proliferation of technology, including the use of social network sites (SNS). Social network sites facilitate communications between online users with shared interests and enable users to share content seamlessly. Accordingly, the rapid growth of social network site usage necessitates analysis of factors affecting usage of SNS and the creation of social networks on the social network sites. A research model that focuses on social capital in SNS and the development of community in SNS is proposed in this paper. The model suggests how the configuration of SNS and the diversity of SNS users influence different relational facets of social capital such as trust, reciprocity and identification needs in SNS and the sense of community in SNS. We conducted a web-based survey to collect the data to test our hypotheses. We find that SNS users interaction needs and trust in interaction have positive relationships with reciprocity in SNS interactions. We also find that the development of the sense of community promotes effective communication in SN