Lakshmanan Ramanathan and Sundaresan Krishnan
The purpose of this paper is to identify the influence of outsourcing on open-source software (OSS) and further investigate the factors that impact the adoption of OSS in global…
Abstract
Purpose
The purpose of this paper is to identify the influence of outsourcing on open-source software (OSS) and further investigate the factors that impact the adoption of OSS in global information technology (IT) outsourcing organizations serviced by Indian IT services organizations.
Design/methodology/approach
The authors developed a conceptual model that describes the factors influencing the OSS adoption by using the technology-organization-environment framework. This quantitative explanatory study used self-administered questionnaire to collect data from 482 middle and top management employees of Indian IT services organizations. The authors analyzed the data using partial least squares to test this conceptual model.
Findings
The proposed conceptual model identified the factors which play a significant role in OSS adoption such as reliability, legal concern, software costs, management support, OSS support availability and software vendor. In contrast, this study did not find enough evidence that IT outsourcing was a significant determinant of OSS adoption.
Research limitations/implications
The main limitation of the research is that it is focused on global IT outsourcing organizations (clients) serviced by Indian IT services providers (vendors). Hence, the authors cannot generalize the finding to other regions. Also, the analysis is based on the view point of employees in vendors. Views of clients’ employees must be analyzed and triangulated with current evidence.
Practical implications
IT services providers can offer “OSS as a service” for its clients and help them address the gaps in support availability and achieve reduction in total cost of ownership of software.
Originality/value
IT services providers can use this research model to increase their understanding of why some IT outsourcing organizations choose to adopt OSS, while seemingly similar ones facing similar market conditions do not.
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Girish Prayag, Martin Landré and Chris Ryan
The purpose of this study is to assess the evolution of restaurant locations in the city of Hamilton over a 12‐year period (1996 to 2008) using GIS techniques. Retail theories…
Abstract
Purpose
The purpose of this study is to assess the evolution of restaurant locations in the city of Hamilton over a 12‐year period (1996 to 2008) using GIS techniques. Retail theories such as central place, spatial interaction and principle of minimum differentiation are applied to the restaurant setting.
Design/methodology/approach
A database of restaurants was compiled using the NZ yellow pages and contained 981 entries that consisted mainly of location addresses and types of cuisine. This paper focuses on locational patterns only.
Findings
A process of geo‐coding and clustering enabled the identification of two clustering periods over 12 years for city restaurants, indicating locational patterns of agglomeration within a short walking distance of the CBD and spill over effects to the north of the city.
Research limitations/implications
The data do not allow statistical analysis of the variables causing the clustering but offer a visual description of the evolution. Explanations are offered on the possible planning regimes, retail provision and population changes that may explain this evolution.
Practical implications
The findings allow identification of land use patterns in Hamilton city and potential areas where new restaurants could be developed. Also, the usefulness of geo‐coded data in identifying clustering effects is highlighted.
Originality/value
Existing location studies relate mostly to site selection criteria in the retailing industry while few have considered the evolution of restaurant locations in a specific geographic area. This paper offers a case study of Hamilton city and highlights the usefulness of GIS techniques in understanding locational patterns.
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Virgilija Vasiliene-Vasiliauskiene, Aidas Vasilis Vasiliauskas, Rišard Golembovskij, Ieva Meidute-Kavaliauskiene, Edmundas Kazimieras Zavadskas, Audrius Banaitis and Kannan Govindan
The purpose of this paper is to develop a better understanding of how transportation system factors affect city housing markets. The goal was to show that identifying these…
Abstract
Purpose
The purpose of this paper is to develop a better understanding of how transportation system factors affect city housing markets. The goal was to show that identifying these factors alone is not enough without also examining their effects and variations according to the housing location.
Design/methodology/approach
Transportation system factors were identified by conducting a thorough literature review. The factors’ relevance was tested using a quantitative methodology and a sample of 317 Vilnius residents. This city was next divided into three zones, and data collected from 18 real estate experts was subjected to qualitative analysis. The analytic hierarchy process was then applied to identify transportation system factors’ level of impact and dynamics by the housing location.
Findings
The results show that the factors affect the housing market in question but that these effects vary by the housing location and the most critical factors differ for each city zone.
Research limitations/implications
Only data on Vilnius were used. Further research is needed to compare transportation factors’ dynamics in multiple cities.
Practical implications
Priorities in transportation system improvements should be assessed to facilitate sustainable urban development and enhance the residents’ quality of life. Housing market regulations can only be successful if investment in transportation systems is allocated purposefully and coherently.
Originality/value
This research went beyond identifying transportation system factors by employing a broad, systematic approach to clarifying potential options for regulating housing markets through transportation system projects.
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The purpose of this paper is to investigate how matching an ad’s empty space color specifically to that of the advertised product’s color (instead of leaving it white) impacts…
Abstract
Purpose
The purpose of this paper is to investigate how matching an ad’s empty space color specifically to that of the advertised product’s color (instead of leaving it white) impacts consumers’ product buying impulse. It tests two competing hypotheses, where the salience explanation proposes a positive effect of empty space–product color matching on product buying impulse, while the contrast account predicts an opposite effect.
Design/methodology/approach
Data was gathered from US-based MTurk panelists under three experimentally designed studies. The proposed effects were tested across multiple product categories, colors and online advertising formats. Qualitative responses from experienced marketing executives were also assessed for managerial insights.
Findings
Across all studies, findings reveal that using a product-colored (vs white) empty space in an ad increases consumers’ product buying impulse, favoring the salience rather the contrast explanation. Increased ad salience owing to an enhanced exposure to product color (an important sensory aspect), in turn improving the product’s hedonic appeal work as serial processes explaining this effect.
Originality/value
This research is not only the first to investigate the effects of using colored empty space (where limited prior research has only focused on white empty space), but also the first to study its impact on impulse buying intentions. Counter to prior advertising research which suggests using greater contrast by using white empty space to achieve positive effects, this research empirically tests and finds that using a product-colored empty ad space instead has a positive impact on product buying impulse.
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This paper aims to show a long run and causal association between economic growth and transport infrastructure.
Abstract
Purpose
This paper aims to show a long run and causal association between economic growth and transport infrastructure.
Design/methodology/approach
In this study, the authors use ARDL models through the period 1990 – 2020 to investigate the relationship between transport infrastructure and economic growth in India.
Findings
The infrastructure has a positive impact on economic growth in India for the long run. Moreover, Granger causality test demonstrates a unidirectional relationship between transport infrastructure to economic development. Stimulatingly, the paper highlights the effect of air infrastructure statistically insignificant on economic growth in the long and short-run period.
Originality/value
The original outcome from the study delivers an inclusive depiction of determinants of economic growth from transport infrastructure in India, and these findings will help the policymakers to frame policies to improve the transport infrastructure. Hence, it is proposed that the government of Indian should focus more to upsurge the transport infrastructure for higher economic development.
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Raju Guntukula and Phanindra Goyari
This paper aims to evaluate the effects of climate variables on the mean yield and yield variability of major pulse crops in the Telangana state of India.
Abstract
Purpose
This paper aims to evaluate the effects of climate variables on the mean yield and yield variability of major pulse crops in the Telangana state of India.
Design/methodology/approach
Authors have estimated the Just and Pope (1978, 1979) production function using panel data at the district level of four major pulses in nine former districts of Telangana for 36 years during 1980–2015. A three-stage feasible generalized least squares estimation procedure has been followed. The mean yield and yield variance functions have been estimated individually for each of these study crops, namely, Bengal gram, green gram, red gram and horse gram.
Findings
Results have shown that changes in climatic factors such as rainfall and temperature have significant influences on the mean yield levels and yield variance of pulses. The maximum temperature is observed to have a significant adverse impact on the mean yield of a majority of pulses, and it is also a risk-enhancing factor for a majority of pulses except horse gram. However, the minimum temperature is positively related to the mean yields of the study crops except for Bengal gram, and it is having a risk-reducing impact for a majority of study crops. Rainfall is observed to have a negative impact on the mean yields of all pulses, but it is a risk-enhancing factor for only one crop, i.e. Bengal gram. Thus, rising temperatures and excess rainfall are not favorable to the productivity of pulses in study districts.
Research limitations/implications
The present study is based on the secondary data at the district level and is considering only one state. Season-wise primary data, including farm-specific characteristics, could have been better. The projected climate change and its impact on the mean yields and yield variance of pulses need to be considered in a future study.
Originality/value
According to the best of our knowledge, this is the first study to empirically evaluate the impact of climatic variables on the mean yields and yield variability of major pulses in Telangana using a panel data for major pulses and nine districts of 36 years time-series during 1980–2015. The study has given useful policy recommendations.
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Muhammad Iftikhar Ul Husnain, Arjunan Subramanian and Azad Haider
The empirical literature on climate change and agriculture does not adequately address the issue of potential endogeneity between climatic variables and agriculture, which makes…
Abstract
Purpose
The empirical literature on climate change and agriculture does not adequately address the issue of potential endogeneity between climatic variables and agriculture, which makes their estimates unreliable. This paper aims to investigate the relationships between climate change and agriculture and test the potential reverse causality and endogeneity of climatic variables to agriculture.
Design/methodology/approach
This study introduces a geographical instrument, longitude and latitude, for temperature to assess the impact of climate change on agriculture by estimating regression using IV-two-stage least squares method over annual panel data for 60 countries for the period of 1999-2011. The identification and F-statistic tests are used to choose and exclude the instrument. The inclusion of some control variables is supposed to reduce the omitted variable bias.
Findings
The study finds a negative relationship between temperature and agriculture. Surprisingly, the magnitude of the coefficient on temperature is mild, at least 20 per cent, as compared to previous studies, which may be because of the use of the instrumental variable (IV), which is also supported by an alternative robust measure when estimated across different regions.
Practical implications
The study provides strong implications for policymakers to confront climate change, which is an impending danger to agriculture. In designing effective policies and strategies, policymakers should focus not only on crop production but also on other agricultural activities such as livestock production and fisheries, in addition to national and international socio-economic and geopolitical dynamics.
Originality/value
This paper contributes to the growing literature in at least four aspects. First, empirical settings introduce an innovative geographical instrument, Second, it includes a wider set of control variables in the analysis. Third, it extends previous studies by involving agriculture value addition. Finally, the effects of temperature and precipitation on a single aggregate measure, agriculture value addition, are separately investigated.