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Authors analyze a business model (BM) based on organizational performance. BMs are strategic tools used to achieve high performance. This study is based on two characteristics of causal complexity: conjunction and equifinality. Authors also examine the applicability of causal asymmetry in the relationship between BMs and organizational performance.

Generally, the relationship between BM elements and organizational performance is analyzed using a correlational approach. This relationship is marked by causal complexity, which cannot be analyzed via such approach. Authors applied a fuzzy-set qualitative comparative analysis with data from three time-periods and two performance variables for pharmaceutical firms.

Qualitative comparative analysis revealed that high performance resulted from configurations (combinations) of BM elements and not from the effects of individual elements. In addition, multiple configurations are available for achieving high performance. Causal asymmetry was observed in the configuration of the BM elements for high and low performances.

Using qualitative comparative analysis of data sets from three time-periods in the context of the pharmaceutical industry BM, authors integrated the theoretical constructs of causal complexity, namely conjunction, equifinality and causal asymmetry.

Findings related to conjunctions will help managers shift their focus from individual BM elements to combinations of BM elements. Additionally, the findings related to equifinality and causal asymmetry will allow flexibility in designing their company’s BM according to the resource constraints their company faces.

This was one of the first few studies on BMs using the twin indicators of the organizational performance relationship and causal complexity.

An integrated intuitionistic fuzzy (IF) modelling-based framework for examining the performance analysis of a packaging unit (PU) in three different stages has been proposed.

For the series and parallel configuration of PU, a mathematical model based on the intuitionistic fuzzy Lambda–Tau (IFLT) approach was developed in order to calculate various reliability parameters at various spreads. For determining membership and non-membership function-based reliability parameters for the top event, AND/OR gate transitions expression was employed.

For 15%–30% spread, unit’s availability for the membership function falls by 0.006442%, and it falls even more by 0.014907% with an increase in spread from 30% to 45%. In contrast, for 15%–30% spread, the availability of non-membership function-based systems reduces by 0.007491% and further diminishes. Risk analysis has presented applying an emerging approach called intuitionistic fuzzy failure mode and effect analysis (IFFMEA). For each of the stated failure causes, the output values of the intuitionistic fuzzy hybrid weighted Euclidean distance (IFHWED)-based IFFMEA have been tabulated. Failure causes like HP1, MT6, FB9, EL16, DR23, GR27, categorized under subsystems, namely hopper, motor, fluidized bed dryer, distributor, grader and bin, respectively, with corresponding IFFMEA output scores 1.0975, 1.0190, 0.8543, 1.0228, 0.9026, 1.0021, were the most critical one to contribute in the system’s failure.

The limitation of the proposed framework lies in the fact that the results obtained for both reliability and risk aspects mainly depend on the correctness of raw data provided by the experts. Also, an approximate model of PU is obtained from plant experts to carry performance analysis, and hence more attention is required in constructing the model. Under IFLT, reliability parameters of PU have been calculated at various spreads to study and analyse the failure behaviour of the unit for both membership and non-membership function in the IFS of [0.6,0.8]. For both membership- and non-membership-based results, availability of the considered system shows decreasing trend. To improve the performance of the considered system, risk assessment was carried using IFFMEA technique, ranking all the critical failure causes against IFHWED score value, on which more attention should be paid so as to avoid sudden failure of unit.

The livelihood of millions of farmers and workers depends on sugar industries. So perpetual running of these industries is very important from this viewpoint. On the basis of findings of reliability parameters, the maintenance manager could frame a correct maintenance policy for long-run availability of the sugar mills. This long-run availability will generate revenue, which, in turn, will ensure the livelihood of the farmers.

Mathematical modelling of the considered unit has been done applying basic expressions of AND/OR gate. IFTOPSIS approach has been implemented for ranking result comparison obtained under IFFMEA approach. Eventually, sensitivity analysis was also presented to demonstrate the stability of ranking of failure causes of PU.

To meet energy demand and tackle the challenges posed by global warming, Bagasse-based Cogeneration Power Generation (BCPG) plant in sugar mills have tremendous potential due to large-scale supply of renewable fuel called bagasse. To meet this goal, an integrated framework has been proposed for analyzing performance issues of BCPG.

Intuitionistic Fuzzy Lambda-Tau (IFLT) approach was implemented to compute various reliability parameters. Intuitionistic Fuzzy Failure Mode and Effect Analysis (IF-FMEA) approach has been implemented for studying risk issues results in decrease in plant's availability. Moreover, IF- Technique for Order Performance by Similarity to Ideal Solution (IF-TOPSIS) is implemented to verify accuracy of IF-FMEA approach.

For membership and non-membership functions, availability decreases to 0.0006% and 0.0020% respectively for spread ±15% to ±30%, and further decreases to 0.0127% and 0.0221% for spread ±30% to ±45%. Under risk assessment failure causes namely Storage tank (ST3), Valve (VL6), Transfer pump (TF8), Deaerator tank (DT11), High pressure heater and economiser (HP15), Boiler drum and super heater (BS22), Forced draft and Secondary air fan (FS25), Air preheater (AH29) and Furnace (FR31) with Intuitionistic Fuzzy Hybrid Weighted Euclidean Distance (IFHWED) based output scores – 0.8988, 0.9752, 0.9400, 0.8988, 0.9267, 1.1131, 1.0039, 0.8185, 1.0604 were identified as the most critical failure causes.

Reliability and risk analysis results derived from IFLT and IF-FMEA approaches respectively, to address the performance issues of BCPG is based on the quantitative and qualitative data collected from the industrial experts and maintenance log book. Moreover, to take care of hesitation in expert's knowledge, IF theory-based concept is incorporated so as to achieve more accuracy in analysis results. Reliability and risk analysis results together will be helpful in analyzing the performance characteristics and diagnosis of critical failure causes, which will minimize frequent failure in BCPG.

The framework will help plant managers to frame optimal maintenance policy in order to enhance the operational aspects of the considered unit. Moreover, the accurate and early detection of failure causes will also help managers to take prudent decision for smooth operation of plant.

The results obtained ensure continuous operation of plant by utilizing the bagasse as fuel in boiler and also mitigate the wastages of fuel. If this bagasse (green fuel) is not properly utilized, there remains a dependency on coal-based power plants to meet the power demand. The results obtained are useful for decreasing dependency on coal, and promoting bagasse as the green, and alternative fuel, the emission by burning of these fuels are not harmful for environment and thereby contribute in preventing the environment from harmful effect of GHGs gases.

IFLT approach has been implemented to develop reliability modeling equations of the BCPG unit, and furthermore to compute various reliability parameters for both membership and non-membership function. The ranking results of IF-FMEA are compared to IF-TOPSIS approach. Sensitivity analysis is done to check stability of proposed framework.

Delivering vaccines to the children who need them requires a supply chain that is efficient and effective. In most of the developing countries, however, the unknown and unresolved supply chain issues are causing inefficiencies in distributing vaccines. There is, therefore, a great need in such countries to recognize the issues that cause delays in vaccine delivery. With this purpose, the present study aims to identify and analyze the key issues in the supply chain of basic vaccines required to immunize children in developing countries.

Based on a field survey of three states of India, in-depth review of relevant literature and experts’ opinions, 25 key issues were recognized as factors of the vaccine supply chain (VSC) and categorized into five main domains. Using integrated interpretive structural modeling and fuzzy analytic network process approaches, the issues have been prioritized to determine their relative importance in the VSC. In addition, a sensitivity analysis has been performed to investigate the priority stability of the issues.

The results of the analysis show that among the five domains of VSC issues, the economic domain with a weight of 0.4262 is the most important domain, followed by the management (0.2672), operational (0.2222), environmental (0.0532) and social (0.0312).

This study focuses on the prioritization of VSC issues; therefore, the results of the present study can provide direction to the decision-makers of immunization programs of developing countries in driving their efforts and resources on eliminating the most important obstacles to design successful vaccination programs.

To the authors’ knowledge, this paper is first to provide a direction to the decision-makers in identifying and managing important issues through the use of an analytical approach.

The present study identifies and analyses the circular supply chain (CSC) enablers concerned with industrial organizations to understand the interconnectedness of CSC enablers.

Conducting a thorough literature review and utilizing a hybrid approach involving Robust-Best-Worst-Method (RBWM) and Interpretive Structural Modeling (ISM) methodologies, we assess the intensity and connectivity of Circular Supply Chain Enablers (CSCEs), incorporating expert opinions. Additionally, we employ fuzzy-MICMAC analysis to determine the driving-dependent power of the CSCEs.

The study identifies 30 CSCEs in a framework, excluding three low-impact enablers at the initial stage. An additional 30 CSCEs are introduced to enhance the framework for improved implementation. The Fuzzy MICMAC study underscores the high instability of four enablers in the linkage quadrant, signaling that minor adjustments negatively impact organizational performance.

This work holds practical significance for industry researchers and practitioners alike. The initial study introduces a structural hierarchy of CSCEs, aiming to provide a model for academics studying CSC and facilitate its practical implementation.

The demand for energy is increasing massively due to urbanization and industrialization. Due to the massive usage of diesel engines in the transportation sector, global warming is increasing rapidly. The purpose of this paper is to use hydrogen as the potential alternative for diesel engine.

A series of tests conducted in the twin cylinder four stroke diesel engine at various engine speeds. In addition to the hydrogen, the ultrasonication is applied to add the nanoparticles to the neat diesel. The role of nanoparticles on engine performance is effective owing to its physicochemical properties. Here, neat diesel mixed 30% of biodiesel along with the hydrogen at the concentration of 10%, 20% and 30% and 50 ppm of graphite oxide to form the blends DNH10, DNH20 and DNH30.

Inclusion of both hydrogen and nanoparticles increases the brake power and brake thermal efficiency (BTE) of the engine with relatively less fuel consumption. Compared to all blends, the maximum BTE of 33.3% has been reported by 30% hydrogen-based fuel. On the contrary, the production of the pollutants also reduces as the hydrogen concentration increases.

Majority of the pollutants such as carbon monoxide, carbon dioxide and hydrocarbon were dropped massively compared to diesel. On the contrary, there is no reduction in nitrogen of oxides (NOx). Highest production of NOx was witnessed for 30% hydrogen fuel due to the premixed combustion phase and cylinder temperatures.

The purpose of this paper is to understand the effect of basin water depth towards the cumulative distillate yield of the traditional and developed single basin double slope solar still (DSSS).

Modified single basin DSSS integrated with solar operated vacuum fan and external water cooled condenser was fabricated using aluminium material. During sunny season, experimental investigations have been performed in both conventional and modified DSSS at a basin water depth of 3, 6, 9 and 12 cm. Production rate and cumulative distillate yield obtained in traditional and developed DSSS at different water depths were compared and best water depth to attain the maximum productivity and cumulative distillate yield was found out.

Results indicated that both traditional and modified double SS produced maximum yield at the minimum water depth of 3 cm. Cumulative distillate yield of the developed SS was 16.39%, 18.86%, 15.22% and 17.07% higher than traditional at water depths of 3, 6, 9 and 12 cm, respectively. Cumulative distillate yield of the developed SS at 3 cm water depth was 73.17% higher than that of the traditional SS at 12 cm depth.

Performance evaluation of DSSS at various water depths by integrating the combined solar operated Vacuum fan and external Condenser.

Amid the outbreak of coronavirus disease 2019 (COVID-19), supply chains have faltered. This has influenced operational and financial performance and lead to uncertainty in supply and distribution. Therefore, systems measuring supply chain risk and disruption management performance have gained interest. This study explores barriers to supply chain performance measurement during disruptions such as COVID-19.

Based on a survey and literature review, the authors formalise the barriers and rank them using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) fuzzy Višekriterijumsko kompromisno rangiranje (VIKOR) methodology. A total of 14 experts in 11 countries were surveyed. Performance measurement is based on a balanced scorecard.

Fifteen barriers are identified. Based on DEMATEL analysis, the cause–effect relationships among the four scorecard aspects are explored. The customer axis is revealed as the cause, while the financial, internal business and learning/development are identified as the effect of the supply chain performance measurement. Fuzzy VIKOR calculations show that uncertainty of investment, disrupted cash flows and the bullwhip effect are the most critical barriers to measure supply chain performance during outbreaks such as the COVID-19 pandemic.

The study identifies and ranks general barriers; additional research is required to differentiate barriers in specific industrial sectors.

The findings may help develop proactive, resilient supply chain performance strategies to overcome disruptions.

Policy-makers and decision-makers in industrial and service firms can explore these findings to inform strategies for robust supply chains that can resist disruption in risky environments.

This research addresses a knowledge gap in barriers to measure supply chain performance in post-pandemic areas. It is unclear how far firms will measure supply chain performance in terms of learning from disruption patterns, managing financial and customer demand processes in light of COVID-19. This study contributes by explaining the influences among the barriers and exploring them, offering insights from multiple stakeholders.

The present paper examines the barriers hindering the implementation of circular economy practices in Indian automotive industries and identifies the most critical barriers to be eradicated during the circular economy implementation.

Using a questionnaire survey-based analytic hierarchy process (AHP) approach, 21 barriers to circular economy implementation are identified through a literature review and ranked using the opinions of relevant industrial experts.

Barriers, minimal or no proper economic incentives, difficulty in ensuring product quality and costing of CE products are identified as top barriers to be eliminated first to boost the chances of successful implementation of circular economy practices in Indian automotive industries.

The study not only offers a roadmap on the order of elimination of barriers towards a circular economy but also provides insights from industrial experts on how these barriers can be eradicated and the ill effects of each barrier from an automotive industry perspective.

The authors develop a theoretical framework for barrier analysis for circular economy implementation in the Indian automotive sector using the classic AHP approach to identify the most critical barriers against successful implementation. Further, this study offers managerial implications on how these barriers can be eradicated in real.