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The literature on copycat packaging has developed intermittently over a 30-year period, resulting in a divergent and fragmented body of knowledge. This paper aims to synthesise the extant literature to highlight the main developments in the marketing, legal and design fields and, in doing so, contributes to a holistic understanding of the research area and suggests directions for future research.

A systematic literature search retrieved 5,862 articles, and after filtering against explicit criteria, 49 studies were reviewed. These articles were subsequently evaluated and interpreted, producing a synthesis of current research.

The constructs of copycat packaging, including similarity-related concepts, consequences of copycat packaging and mitigating approaches, have been reported across three disciplines of marketing, legal and design, each having its own distinct focus but nonetheless sharing overlapping themes.

This review discusses future directions and proposes a framework of research themes relating to brand enhancement for online purchasing, measurement of brand confusion, reinforcing design features and approaches to mitigating copycat practices.

To the best of the authors’ knowledge, this study is the first systematic review of the literature on copycat packaging. It brings together the latest thinking on copycat packaging and identifies distinct research issues to be addressed in future studies.

The purpose of this study is to explore the awareness, perception and attitude of consumers from Georgia toward smart, active and intelligent packaging of food products.

This study is based on a quantitative research method using a survey questionnaire tool to gather data from consumers in Georgia.

The scope of the sample is restricted to only one developing country. Yet, the research results are still significant in creating knowledge about innovative food packaging from different country contexts and to understanding the acceptance of intelligent active packaging by consumers.

Intelligent packaging facilitates companies with their sustainability efforts by reducing waste and environmental impact. It increases the desirability of products as responds to customer demands and leads to consumer satisfaction. Intelligent packaging can increase trust in bioproducts; for example, it is possible to track and check or monitor the origin of a product and prove that the product producer has really manufactured a bioproduct.

The study contributes to the discussion of the applicability and use of packaging with enhanced features in the food industry. In this respect, the performed pilot study fills the gap in the packaging literature by investigating consumers’ perspectives on intelligent packaging in Georgia – a non-EU, post-soviet, developing country.

Process orientation is important for improving organizational performance. The process view is considered a key enabler of digital transformation, and thus management control systems (MCS) are expected to incorporate this view. However, the existing body of knowledge is fragmented, as different process approaches are often considered independently following a reductionist view of control practices. This paper aims to provide recommendations for further research as well as guidance for practice by a systematic review of the state of research of MC for process orientation. It is based on both a comprehensive view to MC using an MCS package approach and a comprehensive view of process orientation.

A systematic literature review addressing major types of process orientation approaches was performed by applying the comprehensive MC framework of Malmi and Brown. The results were synthesized and propositions were developed.

All components of the MC framework, as well as MCS packages, are highly relevant for process orientation. Propositions regarding configurations of MC for process orientation show directions for future research. However, comprehensive considerations of packages and of individual components, especially cultural controls, remain scarce in the literature.

To the best of the authors‘ knowledge, this paper is the first of its kind to provide a comprehensive, structured overview of MC for process orientation, applying a nonreductionist view, based on an MCS Package approach, and consolidating the so far fragmented view of different process approaches.

This study investigates how consumers perceive the packaging of Philippine coffee social enterprise products and how this impression affects their willingness to purchase based on sensory expectations, brand attitude, product quality perception, and price perception.

Following a positivist research philosophy, this study used empirical methods, surveying 263 coffee consumers. The coffee packaging prototypes varied across material and graphic designs. The data was analyzed statistically using the Friedman test and Spearman correlation.

It was found that packaging elements elicit an equal share of emotional responses. Graphics have a greater impact than materials. Females are more affected by visuals, while materials influence males more. Further, packaging design correlates positively and significantly with consumer impressions and willingness to buy.

The sampling methodology limits generalizability. Future studies can use integrated models to analyze the effects of additional packaging variables like color and shape.

Coffee enterprises should focus on graphic rather than material elements. Paper packs with patterned graphics are most attractive to consumers. Targeted gender-sensitive packaging designs are needed. Standardized packaging can help build the Philippine coffee social enterprise industry and support small-scale farmer livelihoods. Environmentally sustainable materials should be prioritized.

The findings contribute to the success and growth of small-scale farmers and social enterprises in the Philippines. These businesses can attract more consumers, increase their market share, and ultimately generate more significant social impact by implementing packaging design strategies that effectively communicate product quality, sustainability, and social value.

The study uniquely integrates diverse methods to provide holistic insights into jointly analyzing the effects of packaging materials and graphics. It proposes an expanded conceptual role of packaging in shaping product perceptions using the affective response framework and Kansei approach.

This paper aims to investigate how implying movement in food packaging imagery may affect product liking. Furthermore, the underlying mechanism is investigated by studying the effect of implied motion visuals on design appeal and naturalness perception.

Two packages of pineapple juice were designed in which the implied motion depicted in their imagery was manipulated, and a tasting experiment was conducted in which two samples of the same juice were evaluated.

The results show that the effect of packaging imagery on product liking occurs indirectly through both design appeal and the product naturalness perception. The results of a parallel multiple-mediator analysis show that (1) depicting implied motion made the package be perceived as more appealing, (2) the product corresponding to the package depicting implied motion was perceived as being more natural, and (3) both effects equally contributed to the positive effect of visuals depicting implied motion on product liking.

Overall, these findings widen our understanding of the effects of packaging design on product liking and may help both designers and manufacturers design more appropriate packaging for their products.

Existing labor estimation models typically consider only certain construction project types or specific influencing factors. These models are focused on quantifying the total labor hours required, while the utilization rate of the labor during the project is not usually accounted for. This study aims to develop a novel machine learning model to predict the time series of labor resource utilization rate at the work package level.

More than 250 construction work packages collected over a two-year period are used to identify the main contributing factors affecting labor resource requirements. Also, a novel machine learning algorithm – Recurrent Neural Network (RNN) – is adopted to develop a forecasting model that can predict the utilization of labor resources over time.

This paper presents a robust machine learning approach for predicting labor resources’ utilization rates in construction projects based on the identified contributing factors. The machine learning approach is found to result in a reliable time series forecasting model that uses the RNN algorithm. The proposed model indicates the capability of machine learning algorithms in facilitating the traditional challenges in construction industry.

The findings point to the suitability of state-of-the-art machine learning techniques for developing predictive models to forecast the utilization rate of labor resources in construction projects, as well as for supporting project managers by providing forecasting tool for labor estimations at the work package level before detailed activity schedules have been generated. Accordingly, the proposed approach facilitates resource allocation and enables prioritization of available resources to enhance the overall performance of projects.

This paper aims to compare and evaluate the influence of package designs and characteristics on the mechanical reliability of electronic assemblies when subjected to harmonic vibrations.

Using finite element analysis (FEA), the effect of package design-related parameters, including the interconnect array configuration, i.e. full vs perimeter, and package size, on solder mechanical stresses are fully addressed.

The results of FEA simulations revealed that the number of solder rows or columns available in the array, could significantly affect solder stresses. In addition, smaller packages result in lower solder stresses and differing distributions.

In literature, there are no papers that discuss the effect of solder array layout on electronic packages vibration reliability. In addition, general rules for designing electronic assemblies subjected to harmonic vibration loadings are proposed in this paper.

This study aims to investigate public sentiment toward economic stimulus using textual analysis. Specifically, it analyzes Twitter’s public opinion, emotion-based sentiment and topics related to COVID-19 economic stimulus packages.

This study applies natural language processing techniques, such as sentiment analysis, t-distributed stochastic neighbor embedding and semantic network analysis, to a global data set of 88,441 tweets from January 2020 to December 2021 extracted from the Twitter platform, discussing COVID-19 economic stimulus packages.

Results show that in the fourth quarter of 2021, there is a declining trend of positive sentiment (−5%) and an increasing trend of negative sentiment (14%), which may indicate the perceived inadequacy of COVID-19 stimulus measures. Topic modeling identifies seven topics, highlighting the necessity of stimulus in the education sector.

The big-data findings of this study provide a better understanding of public sentiment about economic stimulus for regulators and policymakers, which can help in formulating more effective fiscal and monetary policies.

Public sentiment is a significant concern for regulators because of its associated ambiguity, such as how to design stimulus packages and evaluate the effectiveness of previous measures. This study applies natural language processing, contributing to the growing literature on designing effective economic stimulus.

In recent decades, there has been a significant increase in global concern regarding the impact of economic activities on the environment and climate change. In this context, green entrepreneurship has become a growing trend in the business world. One of the most important benefits of green entrepreneurship is enhancing energy efficiency and resource utilization. By reducing the resources required to produce a product or deliver a service, green entrepreneurship can contribute to cost reduction and operational efficiency improvement. By implementing sustainable business practices, organizations can enhance their image in the eyes of consumers and attract new customers who are environmentally conscious. This chapter addresses the identified gap in the literature regarding the influence of green entrepreneurial activities on organizational financial performance from the perspective of employees in organizations engaged in such activities (waste reduction, waste recycling, energy conservation, air pollutant reduction, packaging reduction, sustainable transportation). Organizational financial performance is measured through perceived performance compared to the previous year and performance relative to expectations. Two visible financial indicators have been selected for analysis: turnover and net profit.

This study aims to investigate the thermal fracture mechanism of moisture-preconditioned SAC305 ball grid array (BGA) solder joints subjected to multiple reflow and thermal cycling.

The BGA package samples are subjected to JEDEC Level 1 accelerated moisture treatment (85 °C/85%RH/168 h) with five times reflow at 270 °C. This is followed by multiple thermal cycling from 0 °C to 100 °C for 40 min per cycle, per IPC-7351B standards. For fracture investigation, the cross-sections of the samples are examined and analysed using the dye-and-pry technique and backscattered scanning electron microscopy. The packages' microstructures are characterized using an energy-dispersive X-ray spectroscopy approach. Also, the package assembly is investigated using the Darveaux numerical simulation method.

The study found that critical strain density is exhibited at the component pad/solder interface of the solder joint located at the most distant point from the axes of symmetry of the package assembly. The fracture mechanism is a crack fracture formed at the solder's exterior edges and grows across the joint's transverse section. It was established that Au content in the formed intermetallic compound greatly impacts fracture growth in the solder joint interface, with a composition above 5 Wt.% Au regarded as an unsafe level for reliability. The elongation of the crack is aided by the brittle nature of the Au-Sn interface through which the crack propagates. It is inferred that refining the solder matrix elemental compound can strengthen and improve the reliability of solder joints.

Inspection lead time and additional manufacturing expenses spent on investigating reliability issues in BGA solder joints can be reduced using the study's findings on understanding the solder joint fracture mechanism.

Limited studies exist on the thermal fracture mechanism of moisture-preconditioned BGA solder joints exposed to both multiple reflow and thermal cycling. This study applied both numerical and experimental techniques to examine the reliability issue.