In today's world the data is considered as an extremely valued asset and its volume is increasing exponentially every day. This voluminous data is also known as Big Data. The Big Data can be described by 3Vs: the extreme Volume of data, the wide Variety of data types, and the Velocity required processing the data. Business companies across the globe, from multinationals to small and medium enterprises (SMEs), are discovering avenues to use this data for their business growth. In order to bring significant change in businesses growth the use of Big Data is foremost important. Nowadays, mostly business organization, small or big, wishes valuable and accurate information in decision-making process. Big data can help SMEs to anticipate their target audience and customer preferences and needs. Simply, there is a dire necessity for SMEs to seriously consider big data adoption. This study focusses on SMEs due to the fact that SMEs are backbone of any economy and have ability and flexibility for quicker adaptation to changes towards productivity. The big data holds different contentious issues such as; suitable computing infrastructure for storage, processing and producing functional information from it, and security and privacy issues. The objective of this study is to survey the main potentials & threats to Big Data and propose the best practices of Big Data usage in SMEs to improve their business process.

Customer purchase intention in online shopping stores can be influenced by electronic word of mouth (eWom) communication generated by the comments of consumers on social networking sites. However, the adoption of eWom information by consumers is influenced by various factors. This study investigates the mechanism through eWom antecedents influence eWom adoption and consumer purchase intention. The study also examines how eWom adoption mediates the impact of antecedents of eWom adoption (Quality, Consumer Attitude, Credibility, Usefulness, Needs, and Adoption) on customer’s purchase intention. Using the hypothetic-deductive approach, the current study used a cross-sectional self-administered survey to collect data from a convenience sample of university students residing in Karachi. The SmartPLS software was used to analyze the collected data. Study findings reveal that all predictors of eWom adoption are significant. It was also found that eWOM adoption mediates the impact of eWom antecedents on consumer purchase intention. The results provide significant implications for website designers and digital marketers. For marketers working with social media, the findings of this study are encouraging. Marketers can use these findings to develop viral marketing campaigns and encourage customers to contribute useful and credible eWom that could improve the customers’ purchase intention.

Sustainable increases in crop production require efficient use of resources, and intercropping can improve water use efficiency and land productivity at reduced inputs. Thus, in a three-year field experiment, the performance of maize/soybean strip intercropping system differing with maize plant density (6 maize plants m-2, low, D1; 8 maize plants m-2, medium, D2; and 10 maize plants m-2, high, D3) was evaluated in comparison with sole maize or soybean cropping system. Results revealed that among all intercropping treatments, D2 had a significantly higher total leaf area index (maize LAI + soybean LAI; 8.2), total dry matter production (maize dry matter + soybean dry matter; 361.5 g plant-1), and total grain yield (maize grain yield + soybean grain yield; 10122.5 kg ha-1) than D1 and D3, and also higher than sole maize (4.8, 338.7 g plant-1, and 9553.7 kg ha-1) and sole soybean (4.6, 64.8 g plant-1, and 1559.5 kg ha-1). The intercropped maize was more efficient in utilizing the radiation and water, with a radiation use efficiency of 3.5, 5.2, and 4.3 g MJ-1 and water use efficiency of 14.3, 16.2, and 13.3 kg ha-1 mm-1, while that of intercropped soybean was 2.5, 2.1, and 1.8 g MJ-1 and 2.1, 1.9, and 1.5 kg ha-1 mm-1 in D1, D2, and D3, respectively. In intercropping, the land and water equivalent ratios ranged from 1.22 to 1.55, demonstrating that it is a sustainable strategy to improve land and water use efficiencies; this maximization is likely associated with the species complementarities for radiation, water, and land in time and space, which resulted in part from competition avoidance responses that maximize the economic profit (e. g., 1300 US $ ha-1 in D2) over sole maize (798 US $ ha-1) or sole soybean (703 US $ ha-1). Overall, these results indicate that optimizing strip intercropping systems can save 20–50% of water and land, especially under the present scenario of limited resources and climate change. However, further research is required to fully understand the resource capture mechanisms of intercrops in intercropping.

Purpose: The central point of this study was to demonstrate the similarity and difference of Human Resource Management (HRM) practices amongst the countries in South Asia. Through this paper, an in-depth study was undertaken to evaluate the validity of existing HRM practices in South Asian (SA) countries. An effort was made to examine the influences from the economic emergence in South Asia, force of colonization, historical panorama, cultural similarities and dissimilarities, legal, economic and political factors causing the change. Methodology/Sampling: The study is based on secondary data collected through extensive research on present and past literature available on the topic. Findings: HRM is in a reforming process towards the development of organizational transformation in South Asia. In addition, contextual and contingency factors are determining the outcome of restructuring HRM practices in South Asia, identified as FDI, foreign MNCs’ influence, and bilateral relations amongst the SAARC members. Practical Implications: Due to cultural impediments, organizations are finding it difficult to implement modern HRM practices in true letter and spirit. This study may draw some lessons for development and collaboration of novel opportunity of SAARC industries’ HRM practices in South Asia.

This study aims to explore in detail the factors that affect the consumer behavioral intention to adopt broadband Internet in a developing country perspective. Various attitudinal, normative, and control constructs were identified and investigated for their possible influence on broadband Internet adoption. The empirical data for this study were collected using a selfadministered questionnaire that included items related to various attitudinal, normative, and control constructs. Descriptive statistics and regression analysis were used to test these constructs for their possible influence on Indian consumers' adoption of broadband Internet. The findings suggest that perceived ease of use (PE), social outcomes (SO), hedonic outcomes (HO), service quality (SQ), facilitating conditions resources (FCR), and self-efficacy (SE) were very significant predictors of Indian consumers' behavioral intention to adopt broadband Internet. This study has multifold significance. The integrated research framework used in this study is an extension of previous well-established research models (such as Model of Adoption of Technology in Households [MATH], Diffusion of Innovation [DOI], and Theory of Planned Behavior [TPB]) and provides an enhanced comprehension of broadband Internet by the Indian household consumers.