This article examines the nexus between Big data governance, dynamic capability and decision-making. Survey data was garnered from firms in Jordan and fuzzy sets (fsQCA) approach was applied. Fuzzy set configural modeling revealed two causal models for high decision-making effectiveness conditions. First, Big data governance, number of employees and firm age are necessary for higher levels of effective decision-making. Second, dynamic capability, number of employees and firm age are necessary for higher levels of effective decision-making. Insights for practitioners in an emerging economy and possible areas of future research are highlighted.

Effective transshipment network is currently recognized as an important success determinant for most manufacturing organizations, because the transshipment management has significant impact on cost and environmental impact. Due to the complexity of the multi-criteria transshipment problem for infectious waste management (IWM) for this case, forty hospitals and three candidate disposal municipalities in Northeastern Thailand, a novel holistic approach (combination of fuzzy AHP, transshipment model and DEA) was developed for solving this problem. We first utilized the fuzzy AHP technique to calculate the location weights of each candidate disposal municipalities. Secondly, a new cost-based transshipment model was formulated and solved in order to provide the set of feasible solutions. These solutions can be viewed as decision making units (DMUs), inputs and outputs. Finally, DEA-CCR model was applied to calculate the efficiency scores of candidate DMUs. The study results demonstrated that the proposed holistic approach can help decision makers (DMs) to choose a suitable transshipment network for IWM. The major advantage of the proposed holistic approach is that both costs and environmental impacts under constraints are focused on simultaneously. Future work will apply the developed approach with other real-world complex problems to enhance the validity of the research output further. For large-size transshipment problems in which an exact solution cannot be found, meta-heuristics must be applied.

In the era of digital manufacturing and highly competitive environment, it is desirable to deliver the right item, right quantity at right time at minimal cost. Under this volatile market environment, the inventory should be readily available at the manufacturing level at the lowest possible cost. Many industries have been conventionally employing traditional ABC analyses based on a single criterion of annual consumption cost for classification of inventory items in spite of other criteria such as unit cost, consumption rate, average inventory cost that may be important in inventory classification. To address such problems, incorporation of Multi-criteria decision making (MCDM) methods is considered an advantage. The present article focuses on a new approach to categorize inventory items using Modified similarity-based method. The proposed method is applied to the inventory data of raw materials from a renowned conveyor belt manufacturing company of West Bengal, India. By using Modified similarity-based method, the items are classified in A, B and C categories. Results obtained from the said method using R program are compared with those of well recognized TOPSIS and AHP methodologies to validate the application of this method for inventory classification.

In this paper, we propose a three-phase multi-attribute ranking approach having as outcomes of the modeling phase what we refer to as net superiority and inferiority indexes. These are defined as bounded differences between the classical superiority and inferiority indexes. The suggested approach herein named MANISRA (Multi-Attribute Net Inferiority and Superiority based Ranking Approach) employs in the aggregation phase a bi-parameterized family of compound averaging operators (CAOPs) referred to as generalized Heronian OWAWA (GHROWAWA) operators having the usual OWAWA operators as special instances. Note that the new defined operators are built by using a composition of an arbitrary bi-parameterized binary Heronian mean with the weighted average (WA) and the ordered weighted averaging (OWA) operators. Also, note that the current developed MANISRA method generalizes the superiority and inferiority ranking (SIR-SAW) method which is known to coincide with the quite popular PROMETHEE II method when the net flow rule is used. With net superiority and inferiority indexes and GHROWAWA operators, we are better equipped to rank rationally prespecified alternatives. The basic formulations, notations, phases and interlocking tasks related to the proposed approach are presented herein and its feasibility and effectiveness are shown in a real problem.

This study develops an empirical investigation of trust antecedents and consequences in creating a collaborative business relationship between distribution companies and retailers in the cosmetics market. A conceptual framework based on trust antecedents as inputs and trust consequences as outputs is designed for both parties. In order to evaluate the performance and effectiveness of each considered trust factor for each party, a fuzzy data envelopment analysis (FDEA) based approach is proposed. In order to demonstrate the applicability of the proposed model, a real-life case study is considered. The required data are collected using interview and questionnaires, and the reliability of the collected data is examined using the Cronbach’s alpha. The obtained results indicate that there is no significant difference between both parties’ tendency towards building a collaborative business relationship based on trust. The results also indicate that information sharing is not an effective trust antecedent for both parties. The “product quality” and “product price” are the most effective trust antecedents for retailers, while the “retailer’s financial conflicts records” along with “length of partnership” are the most effective trust antecedents for distribution companies. Finally, the most effective trust consequences for distribution companies and retailers are “information sharing” and “brand advertising”, respectively.

Closed-loop supply chain management is an effective and efficient solution for a set of activities to retrieve a product from a customer and improve its value or to dispose it. Today, designing and planning a closed-loop chain is an inevitable but difficult task. In this research, a scenario-based modeling approach is presented by considering both forward and reverse flows as a closed-loop supply chains in steel industry. The proposed study also develops a multi-product and multi-period model based on a mixed integer linear programming (MILP) approach for profit maximization. The study also considers uncertainty in the amount of raw material, processing, storage and distribution of several products flow. Uncertainty is associated with the quantity and quality of the products in the reverse flow, which are directly affected by customers and sorting centers, respectively. Finally, the model is deployed in Steel industry with real data. The results show that by increasing the quality level of returned products the need for raw materials is reduced and the total profit of the supply chain is increased.

This paper proposes a two-phase heuristic algorithm to solve the crew scheduling problem of the Megabus Bus Rapid Transit System. In the first stage, a division of the original schedules is performed using a recursive algorithm based on dynamic scheduling. In the second stage, work-shift construction based on graph theory is performed using a pairing algorithm (i.e., matching). The method is validated by applying it to the mass transit system of the Central Western Metropolitan Area (AMCO), operated by Integra SA, which serves 11 routes for a daily total of 2899 trips.

A Convenient and green synthesis of 4H-pyran derivatives via one-pot multicomponent reaction of aromatic aldehydes, malononitrile and ethyl acetoacetate using KOH loaded CaO as a catalyst under solvent free condition is reported. The morphology of the catalyst has been characterized by XRD and TEM. This protocol have numerous advantages like lesser reaction time, environment friendly, low cost, easy to separate, and provide higher yield. The synthesized compounds have been characterized and confirmed by different spectroscopic techniques like ¹H NMR, ¹³C NMR, FT- IR, and LC- MS.

The present study was designed to evaluate the amino acid profiles and anti-nutritional contents of six wild vegetables viz. Cardamine hirsuta, Melothria perpusilla, Cryptolepis sinensis, Persicaria chinensis, Lippia javanica and Polygonum perfoliatum from Assam, India. The total amino acid detected was found the highest in P. chinensis as 25.92 mg/g dry weight (DW) followed by P. perfoliatum (19.68 mg/g DW) and M. perpusilla (14.57 mg/g DW), and the lowest amino acid was observed in L. javanica (0.62 mg/g DW). However, the highest non-essential amino acids (NEAA) were detected in P. perfoliatum (3.89 mg/g DW). Among the NEAA, aspartic acid and glutamic acid were detected in all the six plant species which ranged from 0.01 to 0.33 mg/g DW and 0.02 to o.75 mg/g DW, respectively. In this study, the highest concentration of essential amino acids (EAA) was detected in C. hirsuta (1.72 mg/g DW) followed by M. perpusilla (0.95 mg/g DW) and P. chinensis (0.67 mg/g DW). Besides EAA and NEAA, some other amino acids such as phosphoserine, OH-proline, amino adipic acid, phosphoenolamine, and taurine are the most common which were detected. In the study, variable amounts of anti-nutritional contents were found and discussed herein.

New ruthenium(III) complexes with 3-(Benzothiazol-2-yliminomethyl)-phenol (HL) ligand have been synthesized and characterized with the aid of elemental analysis, IR, electronic, and electron paramagnetic resonance spectroscopic techniques. The binding mode of the ligand and complexes with DNA and their ability to bind DNA have been investigated by UV-vis absorption titration. In addition, the ligand and complexes have been subjected to antioxidant activity tests which showed that HL and its ruthenium(III) complexes possess significant scavenging effect against DPPH and OH radicals. Cytotoxic activities of the ligand and ruthenium(III) complexes showed that the ruthenium(III) complexes exhibited more effective cytotoxic activity against HeLa and MCF-7 cells than the corresponding ligand.