Search results

This paper aims to investigate the impact of consumers’ perception of usability of product packaging on impulse buying in terms of its shape, color, material, label and size.

A structural equation model was used for testing the conceptual model. The present research is an applied research and a descriptive survey. By using non-probability sampling, 388 customers of different malls in Shiraz City (Iran) were selected and surveyed by using questionnaires.

Results showed that appropriate material, shape and labeling of packaging have a significant positive influence on consumers’ perception of usability of product packaging, while color and size of packaging do not have an impact on consumers’ perception of a product usability. Moreover, results showed that consumers’ perception of the usability of packaging has a significant positive influence on impulse buying. Consumers’ mood and time pressure had also positive influence on impulse buying, but their moderating role in their influence of consumers’ perception on impulse buying decision was not supported.

Although this research contributes to the product management literature, it has some limitations. For instance, the research model was tested in only one city in Iran (Shiraz). Besides, it is specific to only two product categories and concentrates mainly on consumers’ mood and time pressure as moderating factors.

To the best of authors’ knowledge, this study is the first research which examines the structural relationship of packaging elements on consumers’ perception of reusability of packaging and impulse buying while considering consumers’ moods and time pressure as moderator variables.

The current study aims to investigate the amount of downward pressure on audit fees and its effect on audit quality.

The research population includes 104 listed companies on the Tehran Stock Exchange. In this study, at first, the audit fees pressure was measured; then, by comparing it with actual audit fees, the pressure on audit costs was calculated. Finally, the hypotheses were tested using logistic regression.

The results of models and hypotheses show that, as expected, during the intensification of sanctions (i.e. during 2010), compared with other years, business entities have exerted more pressure to reduce audit fees; moreover, there is a positive significant relationship between fees pressure and the rate of misstatement (reverse audit quality criterion) at 10 per cent error level during 2010, whereas in years before and after 2010, there is no significant relationship between audit fees pressure and audit quality.

The conducted studies in Iran so far have investigated time pressures imposed on auditors. In this study, the audit fees pressure is investigated.

This study aims to examine performance assessment of organizational units through psychological empowerment (PE) and employee engagement (EE) approach and whether this relationship differs among efficient and inefficient organization units.

This study drew on merging the principal component analysis (PCA), data envelopment analysis (DEA) and partial least square-multigroup analysis (PLS-MGA) to benchmark the performance of organizational units affiliated with Zagazig University in Egypt using PE dimensions as inputs and EE as output. Besides investigating whether PE inputs have the same effect among efficient and inefficient units.

Performance assessment based on independent data showed that all the investigated organizational units are not at the same efficiency level. The results revealed that there are eight efficient units versus seven inefficient ones. Moreover, PLS-MGA results demonstrated that no significant differences concerning the impact of PE inputs on EE between efficient and inefficient units groups. Nevertheless, the effect of these inputs was slightly higher in the former.

Studies on EE performance in the service sector are scarce in the literature, this study is a novel contribution of exploring EE efficiency in Egypt as a developing economy. Specifically, using the PCA-DEA-structural equation modeling approach.

Cement as one of the major components of construction activities, releases a tremendous amount of carbon dioxide (CO₂) into the atmosphere, resulting in adverse environmental impacts and high energy consumption. Increasing demand for CO₂ consumption has urged construction companies and decision-makers to consider ecological efficiency affected by CO₂ consumption. Therefore, this paper aims to develop a method capable of analyzing and assessing the eco-efficiency determining factor in Iran’s 22 local cement companies over 2015–2019.

This research uses two well-known artificial intelligence approaches, namely, optimization data envelopment analysis (DEA) and machine learning algorithms at the first and second steps, respectively, to fulfill the research aim. Meanwhile, to find the superior model, the CCR model, BBC model and additive DEA models to measure the efficiency of decision processes are used. A proportional decreasing or increasing of inputs/outputs is the main concern in measuring efficiency which neglect slacks, and hence, is a critical limitation of radial models. Thus, the additive model by considering desirable and undesirable outputs, as a well-known DEA non-proportional and non-radial model, is used to solve the problem. Additive models measure efficiency via slack variables. Considering both input-oriented and output-oriented is one of the main advantages of the additive model.

After applying the proposed model, the Malmquist productivity index is computed to evaluate the productivity of companies over 2015–2019. Although DEA is an appreciated method for evaluating, it fails to extract unknown information. Thus, machine learning algorithms play an important role in this step. Association rules are used to extract hidden rules and to introduce the three strongest rules. Finally, three data mining classification algorithms in three different tools have been applied to introduce the superior algorithm and tool. A new converting two-stage to single-stage model is proposed to obtain the eco-efficiency of the whole system. This model is proposed to fix the efficiency of a two-stage process and prevent the dependency on various weights. Converting undesirable outputs and desirable inputs to final desirable inputs in a single-stage model to minimize inputs, as well as turning desirable outputs to final desirable outputs in the single-stage model to maximize outputs to have a positive effect on the efficiency of the whole process.

The performance of the proposed approach provides us with a chance to recognize pattern recognition of the whole, combining DEA and data mining techniques during the selected period (five years from 2015 to 2019). Meanwhile, the cement industry is one of the foremost manufacturers of naturally harmful material using an undesirable by-product; specific stress is given to that pollution control investment or undesirable output while evaluating energy use efficiency. The significant concentration of the study is to respond to five preliminary questions.

The purpose of this study is truck scheduling and assignment of trucks to the doors simultaneously since these issues were considered mainly separately in the previous research. Also, the door service time and its impact on truck scheduling were not taken into account, so this research endeavors to cover this gap.

In this research, a novel model has been presented for simultaneous truck scheduling and assignment problem with time window constraints for the arrival and departure of trucks, mixed service mode dock doors and truck queuing. To resolve the developed model, two meta-heuristic algorithms, namely, genetic and imperialist competitive algorithms, are presented.

The computational results indicate that the proposed framework leads to increased total costs, although it has a more accurate planning; moreover, these indicate that the proposed algorithms have different performances based on the criteria considered for the comparison.

There are some limitations in this research, which can be considered by other researchers to expand the current study, among them the specifications of uncertainty about arrival times of inbound and outbound trucks, number of merchandises which has been loaded on inbound trucks are the main factors. If so, by considering this situation, a realistic scheme about planning of cross docking system would be acquired. Moreover, the capacity of temporary storage has been considered unlimited, so relaxing this limitation can prepare a real and suitable situation for further study. Examining the capacity in the front of each type of doors of cross-dock and executive servers are the other aspects, which could be expanded in the future.

In this study, a mathematical programing model proposed for truck scheduling to minimize total costs including holding, truck tardiness and waiting time for queue of trucks caused by the interference of each carrier’s movement. At the operational levels, this research considered a multi-door cross-docking problem with mixed service mode dock doors and time window constraints for arrival and departure time of trucks. Moreover, M/G/C queue system was developed for truck arrival and servicing of carriers to trucks.

This study identifies and ranks the appropriate critical success decision criteria (CSDC) for the bulk order distribution (sharing) amongst multiple manufacturers (suppliers) working as an extended enterprise (EE).

The study deploys a qualitative approach to generate the appropriate decision criteria. The balanced scorecard and Pareto's chart (using Minitab^® version 18) were used for gathering and analysing the pertinent criteria.

The process of evaluating and selecting the right manufacturers is essential. Manufacturer (supplier) selection is no longer decided solely based on cost/price criterion; currently, the quality and delivery criteria prevail. Additional incorporated criteria include price/cost, technical capability, production facilities and capacity, customer satisfaction and impression, geographical location, management and organisation, financial position, environmental concern, performance history, repair service, information technology and communication systems, procedural compliance, labour relation record, reputation, flexibility or diversification, attitude, operating controls, business desire, packaging ability, past business records, trust and loyalty, training aids, complaint handling service, warranties and claim policies, reciprocal arrangements, research and development and innovation, modern slavery concern, sustainable capability, collaborative/partnership and responsiveness. The study proposed a conceptual framework of an EE alongside how manufacturers working as a single virtual entity can consider the supply chain operations reference (SCOR^®) model.

The identified CSDC are suitable for order allocation to domestic manufacturers. The deployed approaches could be extended to the mixed and quantitative approaches for increasing the generalisability.

The study establishes the pertinent CSDC that are important to execute equitable order distribution to manufacturers in an EE framework.