The Institute of Business Administration , Karachi is a regionally acclaimed and distinguished, business administration university in Karachi, Pakistan. According to the Higher Education Commission of Pakistan, The IBA was set up in 1955 in collaboration with the Wharton School of the University of Pennsylvania and is the first business school in South Asia set up on the US MBA model. The school has alumni who are leaders in industry, government, and academia in Pakistan. It started as a business school within the University of Karachi. IBA's status was elevated to become an independent, degree-granting institution in Pakistan in 1994 when it received a charter from the Sindh government. In 2011, the Institute of Business Administration joined a group of seven other top business schools in South Asia, six from India and LUMS from Pakistan when it was awarded the coveted certification by the South Asian Quality Assurance System . Wikipedia.
Wang C.-C.,Institute of Business Administration
Cyberpsychology, Behavior, and Social Networking | Year: 2012
Based on Social Penetration theory, this study explores the topics that bloggers disclose on their blogs, and in the real world. A total of 1,027 Taiwanese bloggers participated in this online survey, which revealed that bloggers self-disclosed nine topics (attitude, body, money, work, feelings, personal, interests, experiences, and unclassified). Further, we examined the depth and width of what bloggers self-disclosed to three target audiences (online audience, best friend, and parents), confirming that their disclosure is significantly different for each of these target audiences. Bloggers seemingly express themselves to their best friends the most, followed by parents and online audiences, both in depth and in width. The "wedge model," proposed by Altman and Taylor (1973), has been extended to online relationships in this study. In comparison to male bloggers, female bloggers seemed to disclose more to their best friends and parents in their daily lives; however, no significant difference was observed in their disclosure to online audiences. Younger bloggers (<20 years old) seemed to disclose a wider range of topics; however, there was no significant difference in the depth of their disclosure on their blogs. Discussions of these results are also presented. © 2012, Mary Ann Liebert, Inc.
Lai M.-C.,Institute of Business Administration |
Yeh C.-C.,Institute of Business Administration
Knowledge-Based Systems | Year: 2012
Due to the fluctuation and complexity of the tourism industry, it is difficult to capture its non-stationary property and accurately describe its moving tendency. In this study, a novel forecasting model based on empirical mode decomposition (EMD) and neural network is proposed to predict tourism demand (i.e. the number of arrivals). The proposed approach first uses EMD, which can adaptively decompose the complicated raw data into a finite set of intrinsic mode functions (IMFs) and a residue, which have simpler frequency components and higher correlations. The IMF components and residue are than modeled and forecasted using back-propagation neural network (BPN) and the final forecasting value can be obtained by the sum of these prediction results. In order to evaluate the performance of the proposed approach, the majority of international visitors to Taiwan are used as illustrative examples. Experimental results show that the proposed model outperforms the single BPN model without EMD preprocessing and the traditional autoregressive integrated moving average (ARIMA) models. © 2011 Elsevier B.V. All rights reserved.
Cheung M.-S.,Williams College |
Myers M.B.,Institute of Business Administration |
Mentzer J.T.,University of Tennessee at Knoxville
Journal of Operations Management | Year: 2010
In global business-to-business markets, shared resources between buyers and suppliers often result in competitive advantages and enhanced relationships between firms. Unfortunately, there is a paucity of research regarding learning capabilities between business partners in a cross-border setting. This study takes the approach to integrate customer value literature into interorganizational learning theory and adopts the often-neglected theoretical perspective of transaction value by contextualizing inter-firm collaboration in terms of relationship learning and value co-creation viewed by both the buyers and sellers in one single study. Through the development of a conceptual framework that examines how global environmental and inter-organizational conditions influence learning capabilities, the study investigates how relationship learning influences relationship value for both supplying and buying firms. Using a survey of 126 cross-border dyads in the industrial chemical, packaging, consumer durable, and apparel industries, the authors show how relationship learning is valued by both buyers and suppliers, and how it is critical when viewing the "supplier as a customer." The results indicate the strategic nature of relationship learning in maintaining cross-border business-to-business relationships. Simultaneously, the findings provide evidence that cultural distance is not a significant influence on the firm's propensity to share knowledge with its global partners. It helps advance our understanding of the significance of cultural-pollination in the era of globalization. © 2010 Elsevier B.V. All rights reserved.
Chalikias M.S.,Institute of Business Administration
Journal of Food, Agriculture and Environment | Year: 2010
The present paper studies the views of the citizens of Pella prefecture concerning the overall development of their region, the priorities that should be given to forest management and the measures required for the establishment of new forests. The sample consists of 370 citizens of Pella prefecture. The non-parametric tests of Friedman, Kruskal-Wallis and Mann-Whitney were used for the data analysis. Most of the respondents believed that agriculture is the primary sector supporting the development of their region, closely followed by livestock. When asked about the sectors that may contribute towards the future development of the Pella prefecture, the majority emphasized the prevailing role of tourism.
Chuu S.-J.,Institute of Business Administration
Knowledge-Based Systems | Year: 2014
Selection of radio frequency identification (RFID) technology is important to improving supply chain competitiveness. The objective of this paper is to develop a group decision-making model using fuzzy multiple attributes analysis to evaluate the suitability of supply chain RFID technology. Since numerous attributes have been considered in evaluating the RFID technology suitability, most information available in this stage exhibits imprecise, subjective and vague. Fuzzy set theory appears as an essential tool to provide a decision framework for modeling imprecision and vagueness inherent in the RFID technology selection process. In this paper, a fuzzy multiple attributes group decision-making algorithm using the principles of fusion of fuzzy information, 2-tuple linguistic representation model, and maximum entropy ordered weighted averaging operator is developed. The proposed method is apt to manage evaluation information assessed using both linguistic and numerical scales in group decision making problem with multiple information sources. The aggregation process is based on the unification of fuzzy information by means of fuzzy sets on a basic linguistic term set. Then, the unified information is transformed into linguistic 2-tuple in a way to rectify the problem of loss information of other fuzzy linguistic approaches. The proposed method can facilitate the complex RFID technology selection process and consolidate efforts to enhance group decision-making process. Additionally, this study presents an example using a case study to illustrate the availability of the proposed method and its advantages. © 2014 Elsevier B.V. All rights reserved.
Rajput Q.,Institute of Business Administration |
Haider S.,Institute of Business Administration
Journal of Web Semantics | Year: 2011
The paper presents a semantic annotation framework that is capable of extracting relevant information from unstructured, ungrammatical and incoherent data sources. The framework, named BNOSA, uses ontology to conceptualize a problem domain and to extract data from the given corpora, and Bayesian networks to resolve conflicts and to predict missing data. The framework is extensible as it is capable of dynamically extracting data from any problem domain given a pre-defined ontology and a corresponding Bayesian network. Experiments have been conducted to analyze the performance of BNOSA on several problem domains. The sets of corpora used in the experiments belong to selling-purchasing websites where product information is entered by ordinary web users in a structure-free format. The results show that BNOSA performs reasonably well to find location of the data of interest using context keywords provided as part of the domain ontology. In case of more than one value being extracted for an attribute or if the value is missing, Bayesian networks identify the most appropriate value for that attribute. © 2011 Elsevier B.V.
Neumann M.,Institute of Business Administration
JASSS | Year: 2015
This paper investigates the contribution of evidence-based modelling to grounded theory (GT). It is argued that evidence-based modelling provides additional sources to truly arrive at a theory through the inductive process of a Grounded Theory approach. This is shown by two examples. One example concerns the development of software ontologies of criminal organisations. The other example is a simulation model of escalation of ethno-nationalist conflicts. The first example concerns early to middle stages of the research process. The development of an ontology provides a tool for the process of theoretical coding in a GT approach. The second example shows stylised facts resulting from a simulation model of the escalation of ethno-nationalist conflicts in the former Yugoslavia. These reveal mechanisms of nationalist radicalisation. This provides additional credibility for the claim that evidence-based modelling assists to inductively generate a theory in a GT approach. © 2015 JASSS.
Anwar N.H.,Institute of Business Administration
Antipode | Year: 2012
A martial state's neoliberal policies opened the nation's frontiers to new forms of globalization. This article investigates the political process that undergirded the military and global capital's sequestration of common land in Karachi and the concomitant contestation by a key civil society organization. Using Foucault's conception of sovereignty and government as an assemblage of authority and strategies of rationalization, this paper analyses the role of state and non-state actors and changing power configurations in a conflict that surrounded the enclosure of a common and its transformation into a securitized zone of consumption in Karachi's Civil Lines. The conflict highlights the nature of the politics of space and citizenship in Pakistan's primary metropolis. © 2011 The Author Antipode © 2011 Antipode Foundation Ltd.
Wosnitza J.H.,Institute of Business Administration |
Leker J.,Institute of Business Administration
Physica A: Statistical Mechanics and its Applications | Year: 2014
Recent research has established log-periodic power law (LPPL) patterns prior to the detonation of the German stock index (DAX) bubble in 1998. The purpose of this article is to explore whether a Langevin equation extracted from real world data can generate synthetic time series with comparable LPPL structures. To this end, we first estimate the stochastic process underlying the DAX log-returns during the period from mid-1997 until end-2003. The employed data set contains about 3.93×106 intraday DAX quotes at a sampling rate of 15 s. Our results indicate that the DAX log-returns can be described as a Markov process. As a consequence, a Langevin equation is derived. Based on this model equation, we run extensive simulations in order to generate 100 synthetic DAX trajectories each covering 3000 trading days. We find LPPL behavior in ten artificial time series. Moreover, we can establish a link between LPPL patterns and ensuing bubble bursts in seven synthetic 600-week windows. However, the LPPL components in most synthetic trajectories differ fundamentally from those LPPL structures that have previously been detected in real financial time series. Summarized, this paper demonstrates that LPPL structures are not necessarily the signature of imitative behavior among investors but can also stem from noise, even though the likelihood of this is extremely low. Thus, our findings confirm with high statistical confidence that the LPPL structures in the DAX development are rooted deeper than only in the random fluctuations of the German stock market. © 2014 Elsevier B.V. All rights reserved.
Ekerhovd N.-A.,Institute of Business Administration
Canadian Journal of Fisheries and Aquatic Sciences | Year: 2010
How would the formation, stability, and success of an agreement on cooperative management between neighbouring coastal states for a climate-sensitive fishery resource be affected by changes in the distribution and accessibility of the resource within the exclusive economic zones (EEZs)? In scenario 1, the blue whiting (Micromesistius poutassou) is harvestable in the EEZs of Norway, Iceland, the Faroe Islands, and the European Union (EU), as well as in the international waters of the Northeast Atlantic and the Norwegian Sea. The Barents Sea is a fringe area for the species, and there are no fisheries for blue whiting there. Hence, Russia is not regarded as a coastal state with respect to the blue whiting fishery. This severely weakens the stability of the coastal state agreement. In scenario 2, the area of distribution of the harvestable stock expands into the Russian EEZ, giving it status as a coastal state with respect to the resource and, thus, a partner in the management agreement. This secures the coastal state coalition the maximum attainable cooperative value and increases the likelihood of a stable coastal state agreement.