Digital technologies play a vital role in daily human life and significantly influence human attitudes toward the adoption of new and attractive lifestyles. The internet has been widely accepted in every modern society, and the act of purchasing products or services over the internet, known as online/internet shopping, has revolutionized business. This study was designed using the technology acceptance model and theory of reasoned action. This study identified important factors such as perceived awareness of security, perceived usefulness, personal innovativeness, and perceived ease of use in purchasing, together with the effects of these factors on online purchasing intentions and the mediating role of consumer attitudes toward online purchasing. The results show that the identified factors are positively and significantly related to consumer intentions and attitudes toward online purchasing. This study has the potential to guide online retailers and managers in expanding online purchasing platforms and in increasing their responsiveness to the need to restructure business models according to new technological developments.

Oil and gas (O&G) supply chain management (SCM) is complex because it deals with different geographic locations to manage demand and supply, transportation, inventory, and distribution. Blockchain technology has created an interesting research gap in the SCM domain, and this study is designed to describe the relevancy of blockchain technology for O&G SCM. SCM is based on agile and lean supply chains (SCs). Agile SC focuses on increasing flexibility and responsiveness to gain competitive advantages, and lean SC is based on eliminating waste and processes to improve firm performance. This study is an initial effort to propose a framework that suggests the implication of blockchain for O&G by providing an overview of O&G SCM. Data were collected from SC managers of O&G companies, and we analyzed the impact of agile and lean SCs on firm performance. The results indicate that agile SC is highly important for O&G industries in comparison to lean SC. This study proposes the key requirements of agile SC and how blockchain can uplift agile SC technology with state-of-the-art properties such as data-driven management, information sharing, data privacy, cyber-security, transparency, smart contracts, visibility, traceability, and reliability, which boost SC agility as well as firm performance.

The South Korean aviation market has grown rapidly since the emergence of Low-Cost Carriers (LCCs), and in response to this emergence, the two Full-Service Carriers (FSCs) of South Korea adopted the airline-within-airline (AWA) model and introduced their LCCs to compete with independent LCCs (ILCCs). A few years back, ILCCs filed a petition against Asiana Airlines, one of the two FSCs in South Korea, as Asiana Air was launching another subsidiary on the model of AWA. This, interestingly, indicates that AWA are doing well in the South Korean aviation market. However, a detailed study is required to evaluate the performance of this model, as in the global market the success of AWA is blurred. This study attempts to shed light on the performance of South Korean AWA, which may provide fruitful insights considering the post-COVID-19 dynamics of the aviation market.

Agricultural industry contributes to the economic backbone of many countries. Major crops like wheat, cotton, and rice stand out as fulfillment for basic commodities as well as profitable crops. Naturally, the consumption of major crops is increasing every year, influencing many countries to import the staple crops to meet the nutritional requirements of individuals, and thereby, keeping pressure on the economies for the years ahead. This research work addresses the development of an accurate consumption forecasting model for time series data. The proposed methodology uses 18 socio-economic and environmental factors and evaluates their impact on major crop consumption in Pakistan. Most influential factors are differentiated by the Linear Regression Model to forecast next year's upshot. The smart results of the model are beneficial for the farmers to cope with the decisive question of next pragmatic crop. The proposed model was compared with a variant of conventional approaches and verified the efficient performance in terms of forecast accuracy.

Planning the power distribution network is critical and challenging; the main challenges include the multiple costs involved, selecting the appropriate locations of different nodes of the network at minimal cost, and minimizing the cost of energy loss for both the primary and secondary networks. Literature on the power distribution network presents different approaches, however, lacks to address the several issues of the complex power distribution networks and many aspects are yet to be explored; for example, the uncertain cost of energy loss. This study intends to address the gaps in the literature by proposing a four-phased approach. In doing so, first, an integer linear programming model is formulated with the objective of cost minimization. Secondly, fuzzy variables are used to tackle the parameters with uncertainty; cost of energy loss. In the third phase, a fine-tuned genetic algorithm (FT-GA) that uses the Taguchi Orthogonal Array is introduced to solve the mathematical model. It is worth mentioning that during the design of the experiment, the input parameters are crossover rate, elite count, and population size. In the last phase, a pragmatic approach is adopted and a Pakistan-based case study is used to validate the proposed model and its implication in real-life scenarios. The results exhibit that our proposed approach outperforms traditional methods like the genetic algorithm (GA) and inter-point methods in terms of fitness function value, number of generations, and computational time. This research contributes at both theoretical and managerial levels and may help decision-makers to design networks more efficiently and cost-effectively in Pakistan, Asia, and beyond.