The Psychology Behind Tech Worker Motivation: From Herzberg to Hybrid

The technology sector has been an engine of innovation and a magnet for top talent—but it also faces high turnover, continuous upskilling demands, and the complexities of hybrid or remote work. In this competitive environment, understanding what truly motivates tech workers is critical. This blog post explores both classic and contemporary motivation theories, with practical insights to help HR leaders, managers, and team leaders craft strategies that drive genuine engagement and job satisfaction among their tech teams.

Revisiting Classic Theories: Herzberg and Beyond

Frederick Herzberg’s model, introduced in the 1950s, remains influential today. It posits two categories of job-related factors:

Hygiene Factors (e.g., salary, job security, working conditions):

These factors do not create job satisfaction on their own, but if insufficient, they can cause dissatisfaction. In tech, market-aligned compensation, safe/effective hardware, and stable workflows are typical hygiene elements.

Motivators (e.g., recognition, responsibility, advancement):

These factors, if well-addressed, foster intrinsic satisfaction—crucial for high creativity, problem-solving, and employee engagement. A software developer who receives kudos for designing an elegant solution experiences a motivational boost that goes beyond simple paycheck satisfaction.

Implication for Tech:

In many tech hubs, salaries and standard perks are high enough to serve as robust hygiene. What often differentiates “best places to work” are the intangible motivators: autonomy, meaningful projects, and clear paths to leadership or specialized expertise.

Contemporary Research: The Job Satisfaction Scale for Tech Workers

This scale emerged from the recognition that developers, engineers, and other tech professionals face unique stressors, such as rapid obsolescence of skills or intense sprint cycles (A Job Satisfaction Scale for Tech Workers: Development and Validation in the Global Context). 

Here are a few highlights:

Communication: The best tech teams often rely on strong cross-functional collaboration. Without the right mediums and managerial support, misunderstandings proliferate.

IT Knowledge: Tech employees want organizations that invest in training, dev tools, and knowledge-sharing. Feeling behind the tech curve is demotivating.

Time Pressure & Cognitive Overload: Soaring project demands and continuous learning can lead to burnout. Effective scheduling, well-managed sprints, and mental health resources help mitigate.

Career Advancement: Most devs or engineers want growth, either in leadership or deeper specializations. Lack of clarity is a big frustration.

Changing Career Aspiration: Tech is volatile. Roles can shift drastically as new frameworks emerge. Employees expect the freedom and mobility to pivot.

Team Player: Collaboration in agile or DevOps is central, so interpersonal synergy is a major satisfaction driver.

Creativity & Innovation: Tech pros appreciate the chance to build new solutions, experiment, and fail-forward with management’s support.

Implication for Tech:

By measuring satisfaction via these factors—rather than generic HR constructs—leaders can zero in on the aspects that matter most, e.g., “Time Pressure & Overload” or “Career Advancement.” A robust assessment can guide targeted improvements.

Adopt or adapt the Job Satisfaction Scale for Tech Workers (JSST).

The JSST is a seven‐factor psychometric scale developed specifically to measure the job satisfaction of tech workers in the global context. Each of the seven factors has associated items (predictors). Responses are captured on a Five‐point Likert scale, ranging from strongly disagree to strongly agree.

Factors and Number of Items

1. Communication (7 items)
2. IT Knowledge (3 items)
3. Time Pressure & Cognition Overload (3 items)
4. Career Advancement (3 items)
5. Changing Career Aspiration (3 items)
6. Team Player (3 items)
7. Creativity & Innovation (3 items)

In total, there are 25 measurable items.

(Note: some studies code from -2 to +2. You can choose your numeric coding, so long as you keep it consistent. The original code for strongly disagree was -2 through strongly agree +2, but the more familiar 1–5 approach works the same.)

Below is a concise version of the JSST questionnaire.

Communication (7 items)

1. My organization’s internal communication during crises keeps me informed about its operating and financial situation.
2. Management regularly conveys its commitment to protect employee welfare and well‐being.
3. When external criticism arises, my management tries to defend employees.
4. I feel inspired by our leadership and thus put in extra effort to promote the organization or satisfy customers, especially in times of crisis.
5. I receive timely responses to my concerns, which heightens my job satisfaction.
6. I serve as a positive ambassador for the organization because of its open communication culture.
7. My organization believes effective employee communication is key to success.

IT Knowledge (3 items)

1. My organization supports continuous upskilling in new technologies or tools.
2. My daily tasks demand a good understanding of relevant IT concepts.
3. The availability of technical resources or training helps me feel more confident in my role.

Time Pressure & Cognition Overload (3 items)

1. The fast‐paced nature of my tech role sometimes overwhelms me mentally.
2. I often work under strict deadlines that create intense pressure.
3. The volume of new information (e.g., software updates or domain knowledge) is challenging to absorb in short time frames.

Career Advancement (3 items)

1. I see clear opportunities for promotion and growth in my organization.
2. My organization provides mentorship, skill building, or leadership programs that support my progress.
3. My efforts are recognized and can lead to meaningful advancement.

Changing Career Aspiration (3 items)

1. I periodically rethink my career path because the tech sector is evolving so quickly.
2. The dynamic nature of technology sometimes alters my long‐term professional goals.
3. Market changes or new tech breakthroughs lead me to consider shifting roles or specialties within the industry.

Team Player (3 items)

1. Collaboration and knowledge‐sharing among teammates is strongly encouraged here.
2. My organization fosters a supportive environment for working in teams.
3. I feel valued when I cooperate and build synergy with colleagues on shared projects.

Creativity & Innovation (3 items)

1. I regularly suggest new methods or solutions for performing tasks.
2. I feel supported to experiment or develop fresh ideas.
3. I have a forward‐thinking mindset to tackle challenges uniquely.

Scoring and Weighting Recommendations

The JSST can be scored at both the individual and group levels. Below is a short summary:

1. Numeric Coding: Optionally, convert a five‐point scale to numeric values (e.g., +2 for Strongly Agree down to -2 for Strongly Disagree). Alternatively, use the usual 1–5 coding.
2. Factor Scores: For each factor, average all item scores. For instance, if Communication has 7 items, sum them up and then divide by 7.
3. Factor Weighting: You can weigh each factor equally, or use the factor’s “variance contribution” from the original JSST validation:
   • Communication: α = 0.507
   • IT Knowledge: α = 0.122
   • Time Pressure & Cognition Overload: α = 0.103
   • Career Advancement: α = 0.084
   • Changing Career Aspiration: α = 0.083
   • Team Player: α = 0.054
   • Creativity & Innovation: α = 0.047

The summation is 1.0. Multiplying each factor’s average by its weighting can produce a more sensitive measure of overall satisfaction.

1. Overall Job Satisfaction: Sum (Factor Score × Weighting) across the seven factors. This yields a single numeric measure. Interpreted as negative vs. positive (if coded from -2 to +2), or from 1–5 if coded in a more typical range.
2. Quartile Interpretation: The scale authors often place results into quartiles (Q1 highest satisfaction, Q8 highest dissatisfaction), though you can adopt typical intervals (e.g., 1–2.5 = dissatisfied, 2.6–3.4 = neutral, 3.5–5.0 = satisfied) if you used the 1–5 coding.

JSST Implementation Notes: 

Individual vs. Group:

• Individual Score: Each participant’s factor scores are weighted and summed.
• Group Score: The group average is typically the mean of individual scores or the average of factor scores across all participants.

Cultural and Inclusion Aspects: The scale is validated globally. Its usage supports D&I (Diversity & Inclusion) by capturing an internationally relevant set of job-satisfaction factors that apply across cultural contexts.

Numerical Ranges:

• 1–5 approach: The overall satisfaction might then be e.g., 4.2 meaning “Quite satisfied.”
• -2 to +2 approach: The overall satisfaction might be e.g., +0.7 meaning “moderate satisfaction” or -1.2 meaning “moderate dissatisfaction.”

Time Pressures: Not all factors weigh equally; “Communication” had a high loading in the original factor analysis. Adjust as needed if your organization sees certain factors as more critical.

Consistency: The validated reliability for the entire scale is Cronbach’s alpha ≈ 0.90

The Advent of Hybrid Work: New Motivational Dimensions

Before the pandemic, remote work in tech was common but not universal. Today, hybrid or remote setups have become the new normal. How do these arrangements intersect with motivation?

Flexibility as a Motivator

Research across multiple industries affirms that flexible scheduling and location independence can improve overall satisfaction if well-managed (Impact of Hybrid Work Model on Job Satisfaction of Techies… 2024). Tech employees typically handle tasks that do not require daily in-person contact, so location flexibility is beneficial.

Key caution: Without structured communication, remote employees can feel isolated, which undercuts “Team Player” factor. Another risk is “digital overload” if Slack messages or Zoom calls are nonstop. Balancing synchronous and asynchronous communication is key.

Reimagining Collaboration and Recognition

In a physically dispersed environment, managers must adopt more deliberate recognition practices—public Slack “kudos,” short video standups, or virtual “demo days.” These gestures can replicate the intangible motivators that tech workers crave (Herzberg’s concept of “recognition”).

Understanding Worker “Profiles”

Not all tech employees respond the same way to these factors. One study identifies at least two clusters:

Achievement & Power-Oriented: Competitive, leadership-driven, aim for consistent performance recognition, and fast promotion.

Affiliation & Collaboration-Focused: Cooperative, appreciate strong team bonds, emphasize synergy.

Implication for Tech:

Provide leadership tracks and advanced performance-based rewards for the “competitive” group, while focusing on robust team events and mentorship for “collaborative” employees. Let them choose from different development “tracks” that reflect these motivational triggers.

Practical Guidelines for Tech Leaders

Step 1: Measure Using Tech-Specific Tools

• Adopt or adapt the Job Satisfaction Scale for Tech Workers (JSST).
• Analyze factor scores (Communication, Time Pressure, etc.) to find areas of friction.

Step 2: Address Overload and Burnout

• Time Pressure & Cognitive Overload: Evaluate sprint length, realistic deadlines, and mental-health offerings.
• Encourage rotation or “cool-down” cycles after intense releases.

Step 3: Provide Clear Advancement Paths

• Lay out dual career ladders: (1) management-oriented; (2) specialized “senior developer / staff engineer” routes.
• Offer ongoing training or certification budget so they keep pace with evolving frameworks or cloud platforms.

Step 4: Enhance Communication and Collaboration

• Encourage routine standups or “show & tell” sessions.
• Use code reviews and knowledge-sharing as a motivational platform—recognition by peers is extremely powerful in tech.

Step 5: Hybrid/Remote Strategies

• Provide flexible scheduling but also have consistent “core hours” for synchronous collaboration.
• Nurture “digital water cooler” chats or Slack channels so that those affiliation-minded techies maintain social connectivity.

Overcoming Common Pitfalls

One-Size-Fits-All: Some leaders simply raise salaries or add standard perks. However, ignoring intangible motivators (like creative freedom) results in partial improvement at best.

Neglecting Culture: If your environment doesn’t reward transparency and knowledge sharing, top devs may still exit, no matter how flexible the schedule.

Failing to Evolve: Tech demands are dynamic. Employees evolve, the market evolves, so your motivational strategies must adapt—especially as new “career aspirations” arise or new frameworks gain traction.

Putting it all together

Today’s tech workforce is driven by a complex blend of intrinsic and extrinsic motivators, from salaries to personal growth, from time flexibility to team synergy. Classical theories like Herzberg’s remain relevant, but specialized scales—like the Job Satisfaction Scale for Tech Workers—bring finer detail to these unique demands: rapid skill changes, potential overload, unstoppable redefinition of roles, and the complexities of hybrid or remote.

For tech leaders, the future calls for targeted motivation strategies—not only must you maintain hygiene factors (competitive pay, stable environment), you also have to nurture advanced motivators like career progression paths, robust knowledge-sharing cultures, creative license, flexible/hybrid structures, and personal recognition. Doing so ensures that your devs, engineers, and data scientists remain deeply engaged, supportive of each other, and eager to push the boundaries of innovation.

Key Takeaway: Effective motivation in the tech sphere is multidimensional—the synergy of fair compensation, growth opportunities, aligned culture, flexible work models, and strong recognition loops all form the potent formula that fosters retention, productivity, and organizational success.

References & Further Reading

Ehigbochie, Amenawon & Ekuobase, Godspower. (2025). Job Satisfaction Scale for Tech Workers: Implementation Compass. FUDMA Journal of Sciences. 8. 466-480. 10.33003/fjs-2024-0806-2999.

Ehigbochie, Amenawon & Ekuobase, Godspower. (2024). A Job Satisfaction Scale for Tech Workers: Development and Validation in the Global Context. Human Behavior and Emerging Technologies. 2024. 1-20. 10.1155/2024/8873743. 

Gangisetty, N. & Dias, Rui & Irfan, Mohammad & Mohana, S. & M, Sandeep & Santosh, Kathari & Galvão, Rosa & Varela, Miguel. (2024). Impact of Hybrid Work Model on Job Satisfaction of Techies during the COVID-19 Pandemic. Journal of Ecohumanism. 3. 977-987. 10.62754/joe.v3i4.3502. 

Arini, Dewi & Hardani, Hardani & Rusmalia, Rusmalia. (2024). Factor Analysis of Innovative Work Behavior in IT Employees with Millennial Generation Characteristics. Syntax Literate ; Jurnal Ilmiah Indonesia. 9. 6739-6751. 10.36418/syntax-literate.v9i11.50116. 

Herzberg, F., Mausner, B. and Snyderman, B. (1959) The Motivation to Work. 2nd Edition, John Wiley & Sons Inc., New York, 20, 141-147.