Investigation of pedestrian crashes using multiple correspondence analysis in India

Abstract

Pedestrian safety is of growing concern with an increasing number of traffic accidents, especially in developing economies like India. In 2017, there were 20,457 pedestrian fatalities in India. Pedestrian crashes have also become a key concern in the state of Tamilnadu, India, due to the high percentage of deaths. If the available datasets are large and complex, identifying key factors is a challenging task. In this study, Multiple Correspondence Analysis (MCA), an exploratory data analysis technique was used to explore the roadway, traffic, crash, and pedestrian-related variables influencing pedestrian crashes. This study used the data from Government of Tamilnadu Road Accident Traffic Management System (RADMS) database, to analyse accident data of nine years (2009–2017) related to pedestrian crashes. The results of the study show that crashes occurring on the express highways on a multilane road are often associated with hit-and-run behaviour among drivers. Factors such as lighting conditions, location, pedestrian behaviour, crossings, and physical separation are also significantly contributing to pedestrian crashes. The key advantage of MCA is that it identifies a possible association between various contributing factors. The findings from this study will be useful for state transport authorities to improve countermeasures for mitigating pedestrian crashes and fatalities.     

Tariffs,Efficiency Wages and Unemployment

The present model embeds a model of intra-industry trade into a labour market, which is characterised by efficiency wages. It is shown that tariff protection of the import competing, home produced brands, may cause the equilibrium unemployment rate to shoot up and instead of protecting the sector may cause it to contract. This is possible when elasticity of demand is high and firms have less market power and thus, protectionist effect of tariffs may get completely reversed.     

Career success schemas and their contextual embeddedness: A comparative configurational perspective

We introduce career success schemas as critical for understanding how people in different contexts perceive and understand career success. Using a comparative configurational approach, we show, in a study of 13 countries, that two structural characteristics of career success schemas—complexity and convergence—differ across country contexts and are embedded in specific configurations of institutional factors. Adopting complexity and convergence as primary dimensions, we propose a taxonomy of career success schemas at the country level. Based on this taxonomy, we contribute to the understanding of subjective career success across countries, discuss the importance of schemas for organisational career systems in multinational enterprises, and propose specific guidelines for future comparative careers research.     

Value-at-Risk in the Presence of Structural Breaks Using Unbiased Extreme Value Volatility Estimator

Journal of Quantitative Economics - We provide a framework based on the unbiased extreme value volatility estimator to predict long and short position value-at-risk (VaR). The given framework...     

Customer Satisfaction with Consumption Systems

ABSTRACT

Purpose: This research examines how satisfaction toward a product and its associated services offered together by a single provider jointly affects behavioral intentions toward the provider.

Design/methodology/approach: In this study, empirical tests were conducted using longitudinal data spanning 5 years from a multinational company that offers both products and associated services as part of a consumption system to their customers.

Findings: Results show a joint congruent effect of product and services satisfaction on behavioral intentions is linear and positive. It appears that offering great service cannot compensate for less-than-adequate satisfaction toward the product. The results further highlight decreasing customer sensitivity to improvements in both sources of satisfaction and imply that focusing on too high levels of one type of satisfaction for their customers can actually be counterproductive for firms.

Research Limitations: Our model was tested using the data obtained from a single firm. Future research could test this model with data from multiple firms in various different industries and establish broader generalizability to the findings.

Practical Implications: Findings provide managers with insights on how to allocate resources across product and service spaces and to manage product and services revenues over time. Results also indicate that customer behavioral intention ratings are more weighted on product quality over the service received by them. However, mere improvements in the product cannot provide the highest desired results and therefore quality improvements in the product need to be complemented by improvements in service quality.

Originality/Value: There is a rapid emergence of the phenomenon of manufacturers providing both products and services as an integrated consumption system to their customers. While the provision of both product and service subsystems by the same firm leads to certain synergies, there are obvious costs to the development of new service capabilities and coordination with existing product capabilities. Our research intends to address this issue.     

Biogeography based optimization for mining rules to assess credit risk

Financial institutions, by and large, rely on the use of machine learning techniques to improve the classic credit risk assessment model for reduction of costs, delivery of faster decisions, guaranteed credit collections, and risk mitigations. As such, several data mining and machine learning approaches have been developed for computation of credit scores over the last few decades. Moreover, the existing rule-based classification algorithms tend to generate a number of rules with a large number of conditions in the antecedent part. However, these algorithms fail to demonstrate high predictive accuracy while balancing coverage and simplicity. Thus, it becomes quite a challenging task for the researchers to generate an optimal rule set with high predictive accuracy. In this paper, we present an effective rule based classification technique for the prediction of credit risk using a novel Biogeography Based Optimization (BBO) method. The novel BBO in the context of rule mining is named as locally and globally tuned biogeography based rule-miner (LGBBO-RuleMiner). This is applied for discovering optimal rule set with high predictive accuracy from the dataset containing both the categorical and continuous attributes. The performance of the proposed algorithm is compared against a variety of rule-miners such as OneR (1R), PART, JRip, Decision Table, Conjunctive Rule, J48, and Random Tree, along with some meta-heuristic based rule mining techniques by considering two credit risk datasets obtained from University of California, Irvine (UCI) repository. It is found from the comparative study that the proposed rule miner in ten independent runs of ten-fold cross validation outperforms all of the aforesaid algorithms in terms of predictive accuracy, coverage, and simplicity.     

A systematic literature review to integrate lean,agile, resilient,green and sustainable paradigms in the supply chain management

The main focus of this study is to conduct a systematic literature review to integrate lean, agile, resilient, green and sustainable (LARGS) paradigms in the supply chain (SC) domain. To achieve this aim, several research questions were designed: First, how to locate LARGS research in context of SC domain? For this, it is important to understand which types of research articles should be selected for the study? Further, where such studies were conducted (geographical location)? Second, what is the focus of research in LARGS paradigm in SCs? For this, it is important to study, which types of industries or sectors have been targeted in literature? In addition, which tools and techniques have been used mostly? Third, what are the current trends in the relationships of LARGS paradigms, among themselves, and with SC performance measures? Fourth, what are the emerging issues, unexplored areas in this field, based on these what could be future research avenues in this subject domain have been proposed? A total of 160 relevant articles published during 1999–2019 were used for analysis. Based on analysis, findings are summarised, and main research issues and possible future research directions in LARGS paradigms in SCs are highlighted.     

Implementing studio-based learning for design education: a study on the perception and challenges of Malaysian undergraduates

Studio-based learning (SBL) is a teaching and learning methodology that combines different learning pedagogies such as social constructivist, problem-based, and active learning to mimic real-world working experience. Traditionally, SBL is practised in architecture and art programmes, however there is a growing number of research in other areas such as computer science, engineering, entrepreneurship and design courses. Nevertheless, in Malaysia, studies have only focused on architecture programmes. Therefore, this study focuses on reporting the experience and challenges of implementing SBL for a design course in the area of Visual Communication. By employing a qualitative methodology, findings show positive perception towards SBL where respondents reported awareness in improved design and communication skills, and increased acceptance towards team work. They found the critique sessions, facilitated their learning progress. Nevertheless, students reported challenges with inept teaching and learning facilities for design work, collaboration and communication breakdown with stakeholders. The study also reports on improvement strategies to enhance students learning experience through SBL.

     

Managing distance in international purchasing and supply: a systematic review of literature from the resource-based view perspective

The aim of this research is to find out how the extant literature on international purchasing and supply management (PSM) covers the elements of capability from the perspective of distance. A priori, we form a framework of capability driving elements and conclude that distance—in its multiple dimensions—is the fundamental management aspect in international PSM. Equipped with analytical frameworks and a bottom–up process for identifying emergent themes, a systematic literature review was conducted on a representative sample of scholarly literature on international PSM, using the NVivo analysis software and a data display as tools. We identify several capability relevant themes from the literature, and provide a distance-based a posteriori conceptualisation of international PSM, founded in the information processing theory, with the source-user, user-user and source-source distance types driving the information processing requirements, and loading avoidance, policy-based and enhancement mechanisms determining the information processing capacity.     

Does diversity matter? A fresh inquiry into the energy,economy and environment nexus

ABSTRACT

The article extends the literature on the nexus among economy, environment and energy by incorporating an index of electricity generation diversity in production and emission functions. The index is mathematically equivalent to Herfindahl–Hirschman index. The index captures substantial information regarding the ongoing energy transition at the global level. The results obtained through pooled mean group estimation, on a dataset of fairly diversified group of countries, indicate that if diversity index increases by a percentage point, per capita income increases by 2.4% and per capita emissions are reduced by 0.71%. This is against the conventional wisdom in favour of specialization. The study has found some interesting long-run causal pathways. Firstly, the causality runs from diversification to income. Secondly, there is a causality running from electricity consumption to specialization. Thirdly, bi-directional causality runs between emissions and specialization. The results have interesting policy implications. The study supports the growth hypothesis that the electricity consumption drives the economy. As this inevitably increases emissions, a better pathway is through diversification. The fossil fuel intensive pathway may have been the preferred choice in the past for countries with low electricity consumption; the diversified portfolio appears to be prudent in the future.