Development of a Survey Combining Lean, Quality, Safety and Culture in Manufacturing

Abstract

Industrial systems such as lean practices, quality systems, workplace safety, and organisational culture are often managed as separate systems; however, in practice, they are interdependent. This study presents a preliminary survey instrument (CiE II) to assess organisational conditions commonly associated with effectiveness in manufacturing systems. A multi-stage refinement process was applied to an initial 107-item survey using pilot data (n = 127) collected from engineering students with work-integrated industry experience. The methodology combined exploratory factor analysis, item response theory, and thematic analysis to improve both statistical and conceptual coherence. The resulting instrument comprised 28 items, making it more suitable for industrial deployment. Analysis of responses (N = 127) identified three common facets that support lean, quality, safety, and culture. These are (i) Integrated Quality and Workflow Management (α = 0.960), referring to workers perceptions that quality standards exist and that they are resourced to meet them; (ii) Safe and Collaborative Work Culture (α = 0.901), referring to perceptions of behavioural norms and that workers will be treated fairly within the team; (iii) Supportive Leadership and Professional Growth (α = 0.852), referring to perceptions that management supports workers’ ongoing professional development. The potential benefit is the provision of a candidate survey that economically covers four key domains of relevance for manufacturing organisations. This has the potential to allow cross-domain correlations and larger-span regression models that integrate the four domains.

1. Introduction

1.1. Context

Industrial engineering seeks to optimise processes within complex production systems. Manufacturing organisations have faced increasing pressure from supply chain instability, evolving regulatory requirements and technological transformation [1,2,3]. These conditions have intensified the need for organisations to maintain efficient performance while adapting to shifting conditions without incurring major performance losses [1,2,3]. Previous research reviewed manufacturing resilience as an entire ecosystem involving both technical and organisational aspects to sustain operation [4].

In this context, organisation resilience refers to the ability of an organisation to have the necessary internal readiness to respond and succeed when confronted by change and disruptions in the external environment [5,6]. Recent trends in the field include the concepts of active and passive resilience [7], the heightened risk of discontinuity in supply chains and recruitment of skilled staff [8], hence, also human capital [9]. In the case of industrial organisations and manufacturing, resilience has a dependency on agility of production process and logistics, hence also on quality systems and lean improvement activities [10,11].

The present study takes a socio-technical systems perspective, which views manufacturing performance as shaped by the interaction between technical systems, work routines, human behaviour, communication, and organisational structures [12]. This perspective is appropriate because the CiE survey integrates operational practices, quality systems, safety practices, leadership, and culture [13]. Related perspectives, including resilience engineering [14] and high-reliability organisational theory [15], similarly emphasise adaptative capacity and anticipation under disruption. Together, these perspectives support a view of manufacturing systems in which operational practices and organisational conditions are examined as interdependent contributors to performance under disruption. However, the objective of the present study is not so much theory-development, nor analysis of existing theories, but rather the need to address an issue in industry whereby multiple different surveys are used to evaluate worker perspectives of operational matters in the areas of lean, quality, safety, and culture.

1.2. Literature on the Interrelation of Lean, Quality, Safety, and Organisational Culture

Within manufacturing organisations, several internal systems are frequently discussed in the literature, such as lean practices (minimisation of waste) [16,17,18], quality systems [19,20], workplace safety management systems [21,22,23], and organisational processes and culture [5,24,25]. Lean practices such as 5S, Kaizen, and Total Productive Maintenance support improved workflow, waste reduction, communication, and problem solving that enhance organisation performance and efficiency [26,27]. Quality systems such as Six Sigma and Statistical Process Control support process standardisation, monitoring and defect reduction [19,28,29]. Similarly, workplace safety systems contribute through hazard awareness, reporting and reliable work practices [21,22,23], while organisational culture and leadership shape collaboration, trust, engagement and willingness to adapt [30,31,32]. These domains are interrelated organisational conditions that may jointly support resilience.

The literature of lean, quality, safety or organisational culture remains fragmented. This is because most studies investigated these facets either in isolation or through pairwise relationships, such as lean and safety [33,34,35] and safety and culture [36,37,38]. This provides a limited understanding of how multiple organisational facets function together. Existing resilience studies have also focused on supply chains [4] or system-level performance indicators such as cost [32], production loss and recovery time [39], rather than on day-to-day organisational practices and conditions. Therefore, there remains a gap between system-level assessment and practice-level understanding of organisational conditions that may support resilience [40,41]. In parallel, resilience research has proposed several measurement approaches and conceptual models to assess the organisational conditions at the system level. For instance, production-oriented models examine how structural and operational configurations influence resilience formation and performance [32] and multi-level frameworks such as resilience scorecards capture resilience through aggregated indicators [42]. Although these approaches provide valuable insights, they are oriented toward performance metrics and provide limited granularity through day-to-day organisational or operational practices.

In manufacturing organisations, lean, quality, safety, and organisational culture each have their own implementation methods, management routines, and traditions [43,44]. However, separately administered surveys limit the ability to examine relationships across these domains, particularly when participant identity is not linked across instruments. An economical integrated survey therefore offers practical value by enabling cross-domain correlation and broader regression analysis across multiple organisational conditions within the same respondent group.

From a measurement perspective, this creates a gap between system-level assessment and practice-level understanding. There is a need to assess the operational practices and organisational conditions systematically. Survey-based approaches are suitable for this purpose as they enable structured data collection across multiple facets and layers. However, transdisciplinary survey instruments remain limited. Existing tools such as the resilience analysis grid (RAG) assess resilience capabilities in terms of responding, monitoring, learning and anticipating [41]. The core industrial ecosystem (CiE) survey represents an attempt to integrate lean, quality, safety and organisational culture into a single measurement instrument. However, it has the limitation of being lengthy, as the instrument comprises 97 questions, raising the risk of creating participant fatigue and limiting usability in practice [45].

1.3. Research Objectives

The objectives of this study were to develop a refined and shortened version of the CiE survey, to assess organisational conditions across lean, quality, safety, and organisational culture in manufacturing systems.

The study combines exploratory factor analysis, item response theory and thematic analysis to identify a conceptual coherent structure. Due to the nature of the dataset, which relied on student responses, this study is presented as a preliminary, rather than definitive development. The structure of the paper is as follows: Section 2 describes the methodology employed for the instrument refinement process. Section 3 presents the factor and thematic interpretation. Section 4 discusses the implications of the findings, proposes a preliminary conceptual framework and identifies limitations. Finally, Section 5 concludes the study.

2. Materials and Methods

2.1. Research Design

This study adopted a multi-stage instrument refinement approach to develop a survey tool to assess organisational conditions in manufacturing systems. The original core industrial ecosystem (CiE) survey [13] consisted of 107 items covering four facets: lean practices, quality systems, workplace safety, and organisational culture.

In order to address the limitations of existing measurement approaches, a mixed-method design was applied. This combined quantitative and qualitative techniques to improve statistical performance and conceptual coherence while preserving the multidimensional structure of organisational conditions. The process included exploratory factor analysis (EFA), item response theory (IRT), and thematic analysis.

2.2. Data Collection

The survey was administered to engineering students at a New Zealand university. Specifically, 2nd and 3rd year students who had completed a minimum of 400 h of industrial work experience were recruited. Ethical approval for this study was granted by the University of Canterbury Human Research Ethics Committee (UC HREC 2024/84/LR-PS). The number of responses received was 127, representing a response rate of approximately 10.6%.

Although the sample consists of students rather than experienced practitioners, respondents had completed structured industry placements and had direct exposure to real manufacturing environments, including shop-floor operations, supervision and organisational practices. The sample was therefore considered appropriate for preliminary survey refinement [46,47]. However, further validation using practitioner samples remains necessary.

Several design features were considered to reduce participation barriers, including multiple recruitment pathways (such as email and posters), anonymous participation, explicit statements that participation would not affect academic outcomes, neutral wording, reminder messages and mobile-friendly access. However, it is possible that respondents with stronger interests in workplace systems, organisational culture, or safety practices were more likely to participate. Therefore, these measures reduced participation barriers but did not eliminate the possibility of nonresponse bias.

2.3. Analysis Approach

The procedure for CiE II survey refinement consists of several stages; refer to Figure 1. The first stage involved FA, which reduced the initial items by identifying key factors and removing the weak loadings. Next, IRT was applied to assess item discrimination and information, and further trimmed the survey to 28 items.

We then applied a thematic grouping approach to the remaining 28 items, along with 10 additional items that were initially excluded from deployment due to a lack of relevant experience. In total, 8 items with overlapped meaning within the same themes were removed to avoid redundancy. Finally, a content validity check was conducted to evaluate whether the refined questions effectively captured the intended constructs. As a result, the survey was refined from 107 items to 35 items compromising 7 demographic items and 28 substantive survey questions. Of the 28 substantive questions, 26 were closed-ended survey items and 2 were open-ended questions. Demographic items were not included in the factor analysis.

2.3.1. Exploratory Factor Analysis

The structure of the survey items was examined using exploratory factor analysis (EFA) to eliminate redundancy [48]. A polychoric correlation matrix was used due to the ordinal nature of the data [49]. Factors were extracted using the minimum residual (minres) approach with varimax rotation to enhance interpretability. The analysis utilised the “fa” function from the “psyc” package in R software (version 4.4.1) [50]. In FA, a weak factor is typically characterised by low factor loadings below 0.3 [51].

2.3.2. Item Response Theory (IRT)

Item response theory (IRT) analysis was performed using a Graded Response Model (GRM) to assess item discrimination and information contribution [52]. From the output, most of the items have discrimination values above 1.5, suggesting strong differentiating between responses with different levels of trait. Items with low discrimination (hence low information) were removed using the threshold of below 0.35 recommended by [53]. At the other end, items with extremely high discrimination values (steep curve) may indicate the risk of being overly sample-specific or overfit. This is a possibility given this study is not large (n = 127); therefore, this might result in small dataset biases. Accordingly, values above 3.0 were used as a conservative screening threshold, following [54].

2.3.3. Thematic Analysis

Thematic analysis (TA) was used to support interpretation and naming of the statistically retained items [55]. Initial coding was undertaken by Coder 1 at the item level, with each item assigned a short conceptual label reflecting its primary meaning, such as management support, safety collaboration or professional development. Coder 2 then reviewed the coded items jointly with Coder 1, focusing on item meaning, redundancies and conceptual overlap. Themes were retained when they demonstrated internal coherence and relevance to the research aim.

However, when there were differences between statistical grouping from EFA and conceptual grouping from thematic analysis, decisions were made conservatively in favour of statistical structure with thematic analysis used primarily to support interpretation and naming. Formal intercoder reliability statistics were not calculated because the thematic analysis was used as a supportive interpretive procedure rather than a standalone qualitative study. Disagreements between coders were resolved through discussion and consensus.

2.3.4. Content Validity Check

Content validity is a preliminary evaluation of whether the content and structure of survey items are suitable for the target population and research objectives [56]. It is often assessed by an expert or potential respondents who provide feedback on whether the survey items are relevant and align with their understanding.

For this study, a final evaluation of the survey was conducted to assess whether the refined survey items were understandable, relevant and contextually appropriate for manufacturing settings. This stage did not constitute full construct validation. Rather, it functioned as a content review of item wording, grammar, and practical relevance. Feedback was obtained from individuals familiar with manufacturing work environments, including a university workshop technician and a former manufacturing worker. Their feedback was used to identify the survey items’ clarity, explicitness, and contextual appropriateness prior to finalising the survey.

3. Results

3.1. Factor Structure

The original survey comprised 97 items. A correlation matrix was computed for all survey items to identify items that were highly correlated, indicating redundancy, or had low correlations, suggesting poor association with the rest of the survey. In this case, the values for all items in the correlation matrix were less than 0.8, indicating that no items were excessively correlated [57]. Consequently, no items were eliminated from the survey based on correlation alone.

The eigenvalues were extracted from the correlation matrix. The corresponding scree plot is shown in Figure 2.

Multiple factor solutions (ten-factor, seven-factor, five-factor, four-factor and three-factor models) were evaluated based on interpretability and internal consistency. Cronbach’s alpha was used to evaluate the internal consistency of the constructs; see

Table 1. Summary of model reliability analysis, showing Cronbach’s alpha for the various models. # indicates values lower than the 0.7 threshold.

Cronbach Alpha	10-Factor	7-Factor	5-Factor	4-Factor	3-Factor
	Version 1	Version 2	Version 3	Version 4	Version 5
Factor 1	0.9618	0.9639	0.9645	0.965	0.960
Factor 2	0.9169	0.9470	0.9391	0.965	0.901
Factor 3	0.9156	0.9023	0.9053	0.9038	0.852
Factor 4	0.8748	0.8926	0.8949	0.7841	-
Factor 5	0.8804	0.8068	0.6764 #	-	-
Factor 6	0.8934	0.8032	-	-	-
Factor 7	0.6860	0.5722 #	-	-	-
Factor 8	0.8032	-	-	-	-
Factor 9	0.6989 #	-	-	-	-
Factor 10	0.6542 #	-	-	-	-

. A threshold of 0.7 was used as a guideline for acceptable reliability [58]. As a caveat, it should be noted that there are arguments that such thresholds lack empirical justification, and deleting items solely to increase alpha could harm both reliability and validity [59,60]. In the present study, the objective was to reduce items while maintaining an acceptable level of reliability, which requires balancing item diversity with internal consistency. Hence, Nunnally’s 0.7 threshold was applied to ensure the scale remained reliable after item reduction.

A three-factor structure was selected as the most appropriate representation of the data, based on improved conceptual clarity, elimination of weak or single-item factors and acceptable reliability across all retained factors. The four-factor structure was dispreferred because the fourth factor had only one item. The items flagged for removal are shown in Appendix A.

The three-factor model was selected due to its stronger internal consistency, absence of weak or unstable factors, and provision of a more interpretable structure than alternative solutions. The factors were interpreted as

• Integrated Quality and Workflow Management (α = 0.960).
• Safe and Collaborative Work Culture (α = 0.901).
• Supportive Leadership and Professional Growth (α = 0.852).

See

Table 2. Three-factor model breakdown. Table shows the loadings for F1, F2 and F3.

Factor 1: Integrated Quality and Workflow Management
Item	Context	F1	F2	F3
L_CI_1	Upgraded tools & machines	0.801	0.211	0.382
L_CI_2	Management supports continuous improvement	0.724	0.169	0.304
L_KANBAN_2	Defined & prioritised tasks	0.629	0.316	0.104
L_KANBAN_3	Workflow adjusted regularly	0.824	0.165	0.165
L_Waste_6	Smooth workflow	0.731	0.346	−0.003
L_Waste_9	Few rejected products & defects	0.682	0.255	0.162
Q_CUL_1	Ownership of quality	0.678	0.144	0.401
Q_CUL_2	Followed quality standards	0.865	0.123	0.150
Q_CUL_3	Equipment inspected regularly	0.750	0.173	0.130
Q_CUL_5	Timely quality concern address	0.771	0.338	0.218
Q_CUL_6	Accessible quality information	0.772	0.245	0.211
Q_CUL_7	Peer involvement in quality	0.675	0.109	0.312
Q_LEAD_1	Funds for quality projects	0.593	0.392	0.347
Q_LEAD_4	Quality focus communicated	0.778	0.267	0.453
Q_LEAD_5	Prompt issue resolution	0.770	0.330	0.084
Factor 2: Safe and Collaborative Work Culture
Item	Context	F1	F2	F3
HS_ENV_4	Cleaning supplies availability	0.393	0.662	0.349
HS_ORG_2	Colleagues support safety	0.297	0.824	0.150
HS_TASK_9	Clear safety goals	0.189	0.696	0.077
OC_ENV_1	Anti-bullying policies	0.293	0.644	0.296
OC_ENV_6	Cultural values respected	0.217	0.684	0.338
Q_COLLAB_1	Team communication	0.338	0.676	0.451
Q_COLLAB_2	Supported collaboration	0.363	0.548	0.528
Q_COLLAB_5	Mutual support culture	0.112	0.583	0.540
Factor 3: Supportive Leadership and Professional Growth
Item	Context	F1	F2	F3
OC_ENV_3	Supervisor support	0.260	0.385	0.752
OC_ENV_7	Boosted motivation	0.225	0.498	0.698
OC_OPP_1	Skills development	0.248	0.186	0.723
OC_OPP_2	Professional growth	0.244	0.212	0.828
OC_PSY_3	Manageable job	0.215	0.469	0.470

for details of factor loadings for the three-factor model.

The factors represent interrelationship facets of how organisations conceptually maintain performance and adapt under varying operational conditions. The high internal consistency should be interpreted cautiously alongside conceptual coverage. This caution is important as Cronbach’s alpha reflects both item interrelatedness and test length, and high consistency may indicate close conceptual alignment among items rather than independent evidence of construct validity [61].

Integrated Quality and Workflow Management reflects the structural and process-level coordination required for stable and efficient operations. Besides items related to efficiency, this factor captures the organisational ability to maintain coherence across processes under changing demands.

Safe and Collaborative Work Culture represents the role of shared norms, trust, and collective responsibility in enabling resilient behaviour. A culture that supports safety and collaboration enhances the likelihood that employees will communicate risks, share knowledge, and respond effectively to emerging issues. This reflects the interaction between the social environment and effective communication.

Supportive Leadership and Professional Growth reflects the leadership practices that promote management support, employment development, and motivation. Hence, a contribution to workforce engagement. This factor suggests that organisational conditions associated with resilient performance are not only structural but also depend on how individuals are supported and developed within the organisation.

Together, these factors suggest that conditions associated with resilience-related manufacturing performance may depend on the alignment of operational systems, leadership practices, and workforce capabilities rather than on any single organisational facet in isolation.

3.2. Item Response Theory

The FA refined survey items were further analysed using the IRT method. Item information curves were plotted for each remaining survey item (n = 47). IICs provide a visual representation of how much information each item provided across different levels of the latent trait (θ). Based on the IIC analysis, items with low information (n = 13) were insufficient to justify their retention. These items were flagged for potential removal. The items flagged for removal are shown in Appendix A; see the IRT column.

However, some items had multiple peaks, indicating that they provide high information at specific points along the latent trait. Unlike low-information items, these items were not removed at this stage. While multiple peaks could suggest that an item is sensitive to more than one latent trait, they were retained for further analysis in Section 2.3.3. Items with well-defined peaks (I(θ) > 1.0) were retained, as they were effective in discriminating between individuals. A selection of curves is shown in Figure 3. Application of the item information curve resulted in several items being flagged for removal, see IIC column in Appendix A.

This process was interesting in that some of the outcomes were counter intuitive. For example, the availability of health and safety training was removed. Likewise, psychological safety and quality training were excluded. It appears that what is happening here is that people’s responses to these questions do not differ very greatly, and hence, there is little information to be gained in asking these questions. Possibly this may be dependent on the jurisdiction, i.e., that these safety practices may be well-established in the area under examination (New Zealand).

3.3. Thematic Structure

The original survey was administered to students, and the above quantitative statistical analyses were applied to the student dataset. However, there are other question items that were not asked to students because of their lack of experience. Hence, it was necessary to evaluate which of these other questions should be included in the shortened survey. The process for doing this was a thematic analysis. The questions admitted to the thematic analysis were (a) all questions that survived the statistical pruning analysis (n = 28), and (b) all questions that were dropped from the deployed survey because they were not relevant to students (n = 10). The process of thematic grouping was based on [56]. Initial descriptive coding was assigned to each item based on the key concept (e.g., employee well-being, management support, etc.). Similar codes were grouped to form themes.

Nine supporting themes were identified through thematic analysis as shown in Figure 4. The themes identified are Quality Standards and Processes, Communication and Transparency, Professional Growth and Skill Development, Job Satisfaction and Engagement, Operational Efficiency and Resource Management, Leadership and Resource Support, Fairness and Inclusivity, Employee Safety Awareness and Empowerment, and Team Collaboration and Support.

There is support for many of the themes in the literature. For example, the implementation of work standards have shown positive influence in operational performance such as weekly output, lead time, and work-in-process reduction [62]. Similarly, quality management systems (TQM) and maintenance standards (TPM) are positively interrelated with just-in-time practices as critical enablers of operational agility and manufacturing performance [28].

Transparent and open communication within organisations is a critical enabler of employee trust and engagement [63,64]. The workers who feel well-informed and included in processes are significantly more productive, exhibit higher morale, and are more willing to actively contribute to improvement initiatives [63,64].

Job satisfaction and employee engagement has been positively associated with organisational culture [65,66]. Engaged employees feel valued and motivated and hence experience increased job satisfaction and performance [67]. Employees who reported higher job satisfaction were more committed to safety management and contributing to improved workplace safety [68], similarly to how higher employee safety awareness has been shown to be positively influenced by safe behaviours [69]. However, employees with unfair treatment such as inequity in pay [70] and lack of interpersonal or procedural fairness [71] could demotivate an employee to engage with safety practices. In such environments, employees are less likely to report hazards and near misses, thereby affecting the safety culture.

The items such as overproduction, unnecessary inventory and storage buildup (under the theme Operational Efficiency and Resource Management) are common issues impacting costs and customer satisfaction [72]. Leadership and Resource Support is one of the success factors in lean implementation [73,74,75].

Each of the 38 items admitted to the thematic analysis was evaluated per the theme to check interpretation. The process is shown in

Table 3. Evaluation matrix for each of the 38 items admitted to the thematic analysis. Item (n) represents a categorical question. (*) represents questions that were dropped from the deployed survey because they were not relevant to students.

No	Context	New Context	Themes	Notes
1	Has your company implemented any lean programs? (Lean is a practice to improve efficiency and effectiveness of process by eliminating waste)	Has your company implemented any lean programs? (Lean is a practice to improve efficiency and effectiveness of process by eliminating waste)	Operational Efficiency and Resource Management	Remained
2	Optimal resources and inventory levels (i.e., the right amount needed without excess stock) are maintained.	Optimal resources and inventory levels are maintained (i.e., the right amount of materials and supplies to do your work without having extra stock).	Operational Efficiency and Resource Management	Further elaborate what is optimal resources and inventory level for clarity
3	My workplace produces minimal products that require rework or repair (i.e., items that do not meet quality standards).	My workplace is good at producing good quality products that rarely need rework or repair.	Operational Efficiency and Resource Management	Rephrased sentence for clarity
4	Management has a clear understanding of the continuous improvement system and actively helps employees to understand and participate.	Management actively helps employees to understand and participate in continuous improvement.	Leadership and Resource Support	Q3 and Q9 were merged as they both address management’s commitment to motivating employee engagement.
5	Machines and tools are regularly upgraded to maintain efficiency and quality.	Machines and tools are regularly upgraded to maintain efficiency and quality.	Operational Efficiency and Resource Management	Remained
6	Work tasks are clearly defined and prioritised to balance workload.	Work tasks are clearly defined.	Operational Efficiency and Resource Management	To reduce confusion, Q5 was rephrased to focus only on the definition of work tasks.
7	The workflow system is reviewed and adjusted regularly to meet changing needs.	The workflow system is reviewed and adjusted regularly to meet changing needs.	Operational Efficiency and Resource Management	Remained
8		My workplace uses quality-systems to ensure high standards and continuous improvement.	Category question	New question
9	Quality improvement projects are usually supported by management through provision of sufficient funds and resources.	Management promptly addresses quality issues and/or supports quality improvement projects.	Leadership and Resource Support	Q8 and Q10 were merged as they share similar ideas about management’s commitment to addressing quality issues.
10	Management regularly communicates the importance of quality to all employees.	-	Leadership and Resource Support	Merged
11	Management promptly addresses any issues that arise related to quality.	-	Leadership and Resource Support	Merged
12	Employees follow established quality standards and procedures.	Employees follow established quality standards and procedures.	Quality Standards and Processes	Remained
13	Inspection and test equipment are regularly inspected and calibrated.	Inspection and testing equipment are regularly serviced and calibrated.	Quality Standards and Processes	Corrected “test” to “testing” and “inspected” to “serviced” for clarity.
14	Quality concerns are addressed in a timely and transparent manner.	Quality information is communicated clearly and promptly to all employees.	Communication and Transparency	Q13 and Q14 were merged as they share similar ideas about the communication and transparency of quality information.
15	Quality-related information is readily available and communicated to all employees.	-	Communication and Transparency	Merged
16	I feel a sense of ownership over quality issues and work to improve them.	I feel a sense of ownership over quality issues.	Employee Safety Awareness and Empowerment	This question was split to focus solely on employee ownership, as Q7 already addressed engagement in continuous improvement.
17	Peer involvement in quality processes is promoted and valued.	Collaboration among teams and peers is encouraged to improve quality processes.	Team Collaboration and Support	Q16 and Q17 were merged as they share similar ideas about collaboration.
18	Cross-functional collaboration is encouraged and supported by management.	-	Team Collaboration and Support	Merged
19	My work team communicates well.	My work team communicates well.	Team Collaboration and Support	Remained
20	There is a culture of mutual support and knowledge sharing.	My work team shares knowledge to support each other.	Communication and Transparency	Rephrased for clarity
21	I feel safe at work.	I feel safe at work.	Employee Safety Awareness and Empowerment	Remained
22	I have easy access to cleaning supplies and equipment.	-	Leadership and Resource Support	Q21 was removed as overlapped with Q1 and Q3.
23	Hazard reports are promptly followed up with corrective actions. *	-	Employee Safety Awareness and Empowerment	Removed
24	I receive adequate training when rotated to a new task.	I receive adequate training when rotated to a new task.	Employee Safety Awareness and Empowerment	Remained
25	My colleagues are supportive in maintaining a safe work environment.	My supervisor and colleagues provide support to help me work effectively and safely.	Team Collaboration and Support	Q24 and Q32 were merged as they both relate to support in the workplace.
26	My current salary aligns with the average salary for my position and industry. *	I am satisfied with my working conditions and/or salary.	Job Satisfaction and Engagement	Q25 and Q27 were merged as they both relate to employee satisfaction with working conditions.
27	My work is distributed fairly. *	-	Fairness and Inclusivity	Q26 was removed.
28	I am satisfied with my working conditions. *	-	Job Satisfaction and Engagement	Merged
29	I feel that my job is manageable.	I feel that my job is manageable.	Job Satisfaction and Engagement	Remained
30	I am confident in my job security. *	I am confident in my job security.	Job Satisfaction and Engagement	Remained
31	My workplace has clear policies to address workplace bullying and harassment.	My workplace has clear policies to handle bullying, harassment and resolve conflicts fairly.	Fairness and Inclusivity	Q30 and Q31 were merged as they share similar ideas about workplace equality policies.
32	Conflicts are resolved fairly in our workplace. *	-	Fairness and Inclusivity	Merged
33	My supervisor or manager helps and supports me.	-	Team Collaboration and Support	Merged
34	My workplace respects and recognises my cultural values.	My workplace respects and recognises my cultural values.	Fairness and Inclusivity	Remained
35	My workplace boosts my motivation and career satisfaction.	My workplace boosts my motivation.	Job Satisfaction and Engagement	Q34 originally combined motivation and career satisfaction, but since career satisfaction was assessed in Q29, it was split to focus only on motivation.
36	My job allows me to develop new technical/ soft skills.	My job allows me to develop new skills.	Professional Growth and Skill Development	Rephrased for clarity
37	I feel that I am growing professionally.	-	Professional Growth and Skill Development	Q36 was removed as it overlapped with Q35.
38	I feel that my contributions are recognized and appreciated. *	My contributions are recognised and appreciated.	Job Satisfaction and Engagement	Rephrased for clarity
39	I feel emotionally attached to this organisation. *	I feel emotionally attached to this organisation.	Job Satisfaction and Engagement	Remained

. The table documents how the items were variously rephrased, merged, deleted, or retained unchanged. Several items were merged where they addressed similar organisational meanings, such as management support, communication practices, or collaboration. Other items were reworded to improve clarity and accessibility. Some questions were removed when they overlapped with other retained items or when their meaning was already represented elsewhere. This resulted in a reduction in the number of items to 28.

In addition, two open-ended questions were devised. The motivation for these was: (i) to provide a focus on innovation and improvement since these underpin many organisational systems including agility and resilience; (ii) to allow workers to provide a freeform response to capture ideas not already represented in the quantitative items; (iii) potential for follow-up semi-structured interviews. Open-ended questions were not addressed individually to all the themes; nonetheless, the two questions were worded to capture elements from multiple themes, such as communication, empowerment, inclusivity, engagement, leadership support, operations, collaboration, and processes. The open-ended questions are

(a)

What can the company do to encourage you to share improvement ideas?

(b)

What do you wish management knew or considered before making changes or improvements in the workplace?

3.4. Shortened Instrument Structure

The full questionnaire administered in this study was shortened, by the above processes, to a ‘Simplified CiE II Survey’. This contains 26 substantive quantitative survey questions, two open-text questions, and seven demographic questions, for a total of 35 questions. The full survey question list is shown in

Table 4. Simplified CiE II Survey.

Demographic
i	Which manufacturing industry does your company primarily operate in?
ii	What is your company size?
iii	What is your job category?
iv	What is your age?
v	How long have you been working with this company?
vi	What is your gender assigned at birth?
vii	Has your company implemented any lean programs? (Lean is a practice to improve efficiency and effectiveness of process by eliminating waste)
Core industrial ecosystem survey [On a scale of −3 strongly disagree to 3 strongly agree]
1	Optimal resources and inventory levels are maintained (i.e., the right amount of materials and supplies to do your work without having extra stock).
2	My workplace is good at producing good quality products that rarely need rework or repair.
3	Management actively helps employees to understand and participate in continuous improvement.
4	Machines and tools are regularly upgraded to maintain efficiency and quality.
5	Work tasks are clearly defined.
6	The workflow system is reviewed and adjusted regularly to meet changing needs.
7	My workplace uses quality systems to ensure high standards and continuous improvement.
8	Management promptly addresses quality issues and/or supports quality improvement projects.
9	Employees follow established quality standards and procedures.
10	Inspection and testing equipment are regularly serviced and calibrated.
11	Quality information is communicated clearly and promptly to all employees.
12	I feel a sense of ownership over quality issues.
13	Collaboration among teams and peers is encouraged to improve quality processes.
14	I feel safe at work.
15	I receive adequate training when rotated to a new task.
16	My supervisor and colleagues provide support to help me work effectively and safely.
17	I am satisfied with my working conditions and/or salary.
18	I am confident in my job security.
19	My workplace has clear policies to handle bullying, harassment and resolve conflicts fairly.
20	My work team communicates well.
21	My work team shares knowledge to support each other.
22	My workplace boosts my motivation.
23	My workplace respects and recognises my cultural values.
24	My job allows me to develop new skills.
25	My contributions are recognised and appreciated.
26	I think my management does a great job communicating, listening to employees, and showing respect.
Open-ended questions
27	What can the company do to encourage you to share improvement ideas?
28	What do you wish management knew or considered before making changes or improvements in the workplace?

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4. Discussion

4.1. Preliminary Conceptual Framework

The proposed framework, as seen in Figure 5, was developed by integrating three levels of analysis: (1) source organisational domains identified in the CiE survey, (2) factor-derived dimensions identified through exploratory statistical analysis, and (3) thematic interpretations used to preserve broader organisational relevance in the Simplified CiE II Survey.

The proposed framework does not specify antecedent, mediator or outcome pathways, nor does it establish the direction of influence between the identified dimensions. Rather, it represents potential areas of interaction and overlap between operational systems, organisational conditions, and workforce experiences within manufacturing settings. Several bridging concepts, such as trust in management, clarity of work processes, and resource sufficiency, emerged as interpretive linkages across factors.

The framework therefore functions primarily as an interpretive mapping tool rather than a tested structural model of resilience. The interpretive structure brings together operational and organisational conditions commonly examined separately in manufacturing research. Further empirical validation using practitioner samples would be required before any directional or causal relationships could be established.

Several bridging linkages emerged repeatedly across domains and factors. For example, clearly defined work standards and documented procedures gave workers a clearer understanding of work expectations, which improved compliance and performance [62,76]. Equipment availability and reliability were found to be essential in supporting stable operation conditions [28,77]. A continuous improvement mindset refers to the ongoing commitment of employees and management to identify, evaluate, and improve work processes through learning [22,34], problem solving [28,62], collaborative participation [31] and knowledge sharing [78,79]. Organisational relationships and information-sharing processes may influence how employees engage with management and build and sustain trust in leadership [33,63,65]. Similarly, poor communication quality can lead to confusion, errors and inefficiencies in the workplace [63,64].

These interpretive linkages were included to illustrate that organisational innovation, agility and resilience may depend not only on formal systems and procedures, but also on broader organisational and interpersonal conditions that shape engagement, adaptability, and workforce participation.

Some of the removed items may also be interpreted as baseline workplace conditions, similar to hygiene factors in Herzberg’s two-factor model of motivation [80]. This interpretation is used cautiously here, as the present study did not test Herzberg’s model directly. Studies have shown that workers’ productivity is highly correlated with their role satisfaction in several aspects, such as poor ergonomic conditions [77], inequitable treatment like pay equity [70], interpersonal, procedural and informational fairness [71], under-benefiting or over-benefiting situations [81] and ineffective workplace communication [64].

Herzberg argued that hygiene factors and motivators operate independently [82] but the findings of this study reveal overlaps between the two. For example, leadership support (hygiene) and team collaboration (motivator) could be interdependent. A study revealed the interdependence between the two factors, such as motivators (team cohesion during crises and a sense of self-importance) being activated when hygiene factors (workplace stability and clarity) are well-established [83]. Another study also found that when people feel a sense of psychological ownership, they are more willing to put in effort and collaborate, even across departments [79]. This study suggests that more fluid interactions between hygiene and motivators, such as transparent communication (hygiene), may indirectly boost engagement (motivator).

At a more foundational level, the analysis also identifies a set of hygiene factors, such as basic safety practices, standard procedures, and essential training. These elements are widely present across organisations and therefore exhibit low variability in the data. While they do not significantly differentiate organisational performance, their absence can undermine both operational stability and workforce engagement.

Overall, the framework provides a preliminary conceptual representation of how organisational and operational elements may cluster around organisational conditions across technical, social and managerial dimensions in manufacturing systems.

4.2. Hygiene Factor as Baseline Conditions

An important insight from the refinement process is the identification of items that were removed due to low statistical variability when responses to these questions do not differ greatly, and hence there is little information to be gained. These include questions related to basic training, standard operating procedures, and general workplace conditions. The removal of these items through IRT analysis suggests that they function as baseline conditions as they are widely present across organisations and therefore provide limited discriminatory power in measurement.

This aligns with the concept of hygiene factors, being a component of motivation is consistent with Herzberg’s two-factor theory of motivation [80]. In Herzberg’s theory, the hygiene factors are necessary for organisational functioning but do not, on their own, drive higher levels of performance or resilience. Their absence may lead to system failure or disengagement, but their presence does not guarantee superior outcomes.

In the present survey, these items were removed due to lack of information content. In deciding to proceed without the above items, a tacit assumption is made that in the geographical area under examination being New Zealand, these hygiene items are either already in place or not relevant to the type of industrial work conducted in that country. As such, the insights captured may reflect contextual factors unique to New Zealand’s regulatory and workplace environment. Nonetheless, practitioners may like to selectively include some of these if they felt their organisation was weak in an area.

From a resilience perspective, this implies that organisations must first ensure these baseline conditions [84,85] are met before higher-order factors, such as collaboration, leadership support, and workflow integration, can effectively contribute to resilience.

4.3. Limitations and Future Research

Several limitations should be acknowledged. This study is based on a sample of engineering students with work placement experiences, which may not fully represent experienced industrial practitioners. Student-based samples may introduce response-quality concerns, including inattentive or low-effort responses [86]. To reduce this risk, the survey included the use of incentives to motivate students’ attention and complete the survey [87], and a “no opinion” response is provided for students who cannot provide a relevant answer to moderate the risk of unreliable responses [88].

Next, the sample size is relatively small, which may affect the stability of the factor structure. Future studies should validate the instrument using larger and more diverse industrial samples such as geographical differences. Studies have shown that national workplace culture such as paternalism, hierarchy and job security [89], as well as industrial practices, regulatory environments, and workforce characteristics, may influence the applicability of the framework. Cross-country validation would further strengthen the generalisability.

In deciding to proceed without the above items, a tacit assumption is made that in the country under examination being New Zealand, these hygiene items are either already in place or not relevant to the type of industrial work conducted in the country or not relevant to the nature of industrial work undertaken by the surveyed cohort. This is because the input data used to develop the IRT was from engineering students working temporary work placements in New Zealand. New Zealand has established health and safety duties for employers, and a high level of enforcement. In addition, the temporary nature of student work may not expose them to issues of longer-term organisational dynamics such as work–life balance, and their roles may not require their input into operational systems. There may also be national cultural differences. In other countries, particularly developing nations, some factors may need to be interpreted with consideration of socio-economic, regulatory and cultural differences.

The current work does not correlate survey responses with organisational efficacy in the four core areas of industrial ecology. Future work with the survey instrument might be applied to seek correlations between the item responses and the efficacy of lean implementation, effectiveness of workplace safety, supportiveness of organisational culture, and integrity of quality systems. This could be useful to develop a business scorecard. With the accumulation of responses from multiple organisations, it might be possible to provide guidance to any one organisation on its gaps and areas for improvement.

5. Conclusions

This study presents the development and refinement of a survey instrument (CiE II) for assessing organisational conditions associated with resilience in manufacturing systems. Through a multi-stage refinement process combining factor analysis, item response theory, and thematic analysis, the original survey was reduced to a more concise instrument (I = 28 items excluding demographic), hence better suited to industrial deployment. The potential benefit is the provision of a candidate survey that economically covers four key domains of relevance to manufacturing organisations: lean, quality, safety, and culture. This has the potential to allow cross-domain correlations and larger-span regression models that integrate the four domains.

Analysis of responses (N = 127) identified three common facets that support lean, quality, safety, and culture. These are (i) Integrated Quality and Workflow Management, which refers to workers’ perception that quality standards exist and that they are resourced to meet them; (ii) Safe and Collaborative Work Culture, referring to perceptions about behavioural norms and that workers will be treated fairly within the team; (iii) Supportive Leadership and Professional Growth, referring to perceptions that management support the ongoing professional development of the worker.

These facets are interpreted as organisational conditions that may support resilience performance in manufacturing contexts. The study contributes an initial framework for assessing operational, cultural and leadership-related conditions associated with resilience.

Future research could extend this work by validating the instrument in industrial settings and examining its stability across contexts and investigating its relationship with organisational performance and resilience outcomes.